Report on Departmental Activities

Report on Departmental Activities2015

Audio-Watermarking Based Ownership VerificationSystem Using Enhanced DWT-SVD Technique 1. INTRODUCTIONDigital watermarking scheme has been an effective method of hiding information into a digital media. It can applied to different types of media such as text, image, audio and video with the aim of protecting copyright or verifying the media ownership. Of these, the audio ownership verification is of interest in this paper. However, the digital revolution in audio industry has brought new ownership verification challenges, as a recording audio can be copied and distributed easily. A number of digital audio watermarking techniques/ methods have therefore proposed to solve or mitigate the impact of these challenges [1] [10].In digital watermarking, we can hide data in another object (cover data) then send the watermarked object over the internet. Other approaches used for audio ownership verification is known as audio fingerprinting [1]. In these methods, the audio features of a certain audio signal are extracted and saved in a database as original audio fingerprint. Unlike fingerprinting, the watermarking techniques can be implemented in spatial domain where the watermark can be embedded directly into a digital media and modified its values. Alternatively, the digital media can be transferred to a frequency domain where the embedding process takes place [2], [3]. Ramakrishnan et. al. [4] suggested an image watermarking which uses Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) techniques to improve robustness of still images. Lalitha et. al. [5] compared performance of the Discrete Cosine Transform (DCT) and SVD based audio watermarking with the DWT-SVD based audio watermarking and concluded that the DWT-SVD had demonstrated better experimental results than the DCTSVD techniques. Unlike human visual systems, the human auditory systems are much more sensitive and therefore, it is more difficult to achieve the necessary imperceptibility [6], [7]. Moreover, audio signals are typically represented by much less samples per time period, which makes it more difficult to embed the same amount of information robustly and imperceptibly. The number of research in audio watermarking is therefore relatively limited due to the sensitive properties of both the human auditory system and audio signals. zer et. al. [8] proposed SVD based technique to watermark audio signals with minimal effect on the original audio signal. Al-Haj and Mohammad [9] reported a digital audio watermarking technique based on a combination of DWT-SVD techniques with the aim of improving watermark robustness against different signal attacks.In audio copyright-ownership verification systems, however, the watermarking technique should not only satisfy robustness requirement but other important requirements such as imperceptibility to ensure minimal distortion in the audio signal, and uniqueness and immutability features to differentiate between the owner and other parties who claiming the copyright. Al-Yaman et. al. [10] extended the work reported in [9] by using an effective code assignment method to improve quality of the watermarked audio signal through minimizing the effect of the ones in the digital pattern of the embedded digital watermark. Size of the required minimum audio signal cover was also improved by using a hash function encoding method.In this paper, we propose an enhanced audio ownership verification system which builds on the findings reported in [10]. The suggested enhancements which include a new audio signal framing, DWT matrix formation, and embedding methods aim at improving the minimum audio cover period, quality of the watermarked audio and its robustness against various attacks. The remainder of this paper is organized as follows: Section 2 overviews the process of audio watermark embedding extraction into/from the original audio signal. The proposed modifications/enhancements are detailed in Section 3. In Section 4, the obtained experimental results are presented and compared with those obtained by the old system. Finally, Section 5 concludes the work and findings presented in this paper.

2. SYSTEM OVERVIEWFig. 1 shows an overview conceptual diagram for the proposed audio ownership verification system. As illustrated, the watermark (image or a logo) that refers to the owner is embedded into the audio file in a way that it should not affect quality of the original audio. This is achieved by considering an enhanced framing and DWT matrix formation. The ownership of the audio under verification can then be verified by comparing the provided watermark image with that embedded in the audio signal. The proposed watermark embedding/extraction processes can be outlined briefly as follows.

Figure 1. System overview.A. Watermark Embedding ProcessThe watermark embedding process into an audio signal proceeds through the following steps: sampling the original audio signal, partitioning the obtained samples into frames (framing), a four-level DWT is then performed. Next, the obtained DWT is decomposed using SVD technique. The SVD is a numerical technique used to transform matrices into series of linear approximations that expose the underlying structure of the matrix. Mathematically, for example, the SVD of an nn matrix A is defined by the operation [10], [11]:A = U S VT ----------------------------(1)In matrix form, Eqn. (1) can be presented as [9]:----------------------------------(2)The watermark of a digital-image is then encrypted using SHA-1 hash algorithm [10] and embedded into the DWTSVD- transformed audio signal according to the following formula [9]:-----------------------------------(3)where W(n) is the hash bit (0 or 1) of the watermark image, _ is the watermark intensity, S1,1 is the top left value in the S-matrix, and S1,1w is the watermarked S1,1. For example, if _ is set to 0.1, as a selected watermark intensity value, then S1,1 w will equal (1.1 S1,1) when W(n) is 1, and to (S1,1) when W(n) is 0. Now, to produce the desired watermarked audio, the inverse of SVD and DWT is performed. The implemented stages of watermark embedding are shown in Fig. 2 [10]. In the present work, the framing, matrix formations and embedding stages represent the core enhancement suggested in this work,B. Watermark Extraction ProcessThe extraction procedure of the encrypted watermark image from the watermarked audio signal can be achieved by following a process similar to that of the watermark embedding described above. The implemented stages of watermark extraction are shown in Fig. 3.

Figure 2. The Watermark Embedding Process.

Figure 3. The watermark extraction process.C. Ownership Verification ProcessThe extracted bits are compared with those obtained from applying the Hash (SHA-1) on the watermark. The system confirms verification when the compared bits completely match. This procedure is shown in Fig. 4.

Figure 4. Ownership verification process.

3. THE PROPOSED ENHANCEMENTSThis section is devoted to explain the suggested enhancements of the audio ownership verification system under consideration. As mentioned earlier in Section 1, these enhancements which focuses on the audio signal framing, matrix formation and embedding methods aim at improving the minimum audio-cover period, quality of the watermarked audio and its robustness against various attacks. The suggested enhancements and their impacts on improving the system are described as follows.A. Framing of Audio SignalWhen applying the watermark to all frames, the signal-to noise ratio of the audio signal will be degraded. Applying the watermark on selected frames will therefore improve quality of the watermarked audio signal. In addition, since noise is random and might affect only part of the audio signal, the probability of losing the watermark will be decreased. For example, using a sampling frequency of 44100 samples per second, the audio signal is portioned into frames, each of length 800 samples. Selection of this frame length ____ improved the minimum audio-cover period when compared with the minimum periods reported in [9] and [10]. A frame group is then be selected by taking one frame and skipping 29 others. According to the Eqn. (4), the skipped frames allow for adding 1.84 watermark bits in each second.Bit per second =-----------------------------(4)where __ is the sampling frequency, __ is the frame length and __ is the number of skipped frames. The suggested frame selection method is illustrated in Fig. 5.

Figure 5. Audio segmentation scheme.Such a frame selection method minimizes the required audio-cover period by 69% when compared to that reported in [10] and the suggested bit- assignment stage is therefore no longer needed. This improvement is achieved irrespective of the watermark size. Table 1 shows different watermark size examples and the required minimum audio-cover period for both the old and suggested methods.

TABLE 1. Minimum audio-cover period versus watermark size.B. Matrix formationThe discrete wavelets transform (DWT) is a discipline capable of giving a time-frequency representation of any given signal starting from the original audio signal S, DWT produces two sets of coefficients .The approximated coefficients A (low frequencies) are produced by passing the signal S through a low pass filter. The details coefficients D (high frequencies) are produced by passing the signal S through a high pass filter. Depending on the application and the length of the signal, the low frequencies part might be further decomposed into two parts of high and low frequencies. Fig. 6 shows 4-level DWT decomposition for the signal S. The original signal S can be reconstructed using the inverse DWT process [9]. Now, having the same D component repeated several times in the matrix formation reported in [9], [10] may cause a mathematical problem when performing the inverse SVD since it changes the watermarked signal matrix and the correct value of appropriate D cannot be identified due to the repeated values for the same D [11]. A four-level DWT transformation is therefore performed on each frame to produce five multi-resolution sub-bands:D1, D2, D3, D4 and A4, as illustrated on Fig. 6.

Figure 6. Four-level DWT decomposition.These sub-bands are re-arranged in a new matrix form as shown in Fig. 7. The matrix size is obtained from:Matrix --------------------------------(5)where L is the frame length. In this matrix form, unlike the previous matrix form, there will be no repeated values for the same D.

Figure 7. The suggested matrix formation.C. Embedding ProcessRobustness of a watermark increases with the increasing values of watermark intensity (_) in Eqn. 3.Using large values of _ will make the watermarked audio more immune to noise and attacks and easier to extract. In contrast, using smaller values of _ will increase the probability of losing the embedded watermark bits. However, increasing _ will cause SNR to be decreased, as shown in Fig. 8. Based on this, selection of optimum value of _ will be a compromise between quality and robustness. Fig. 9 shows how robustness increases with increased values of _.

Figure 8. SNR versus watermark intensity (_).

Figure 9. Robustness versus watermark intensity (_).

4. RESULTS AND DISCUSSIONIn this section, the impact of the suggested enhancements on the quality of watermarked audio signal is presented and compared with that of the old system. As mentioned earlier, the encoding stage resulted in a clear enhancement on the inaudibility of the watermark. This enhancement is noticeable by listening to the watermarked audio and confirmed by the Signal to Noise Ratio (SNR) measurement. Fig. 10 shows SNR test for embedding watermarks of random different sizes in an audio file of 4:22 minute period. In this example, the signal quality improvement by the proposed system is clearer when compared to the old system.

Figure 10. SNR for watermarks of different sizes.Another performance comparison between the old and suggested systems is shown in Fig. 11. This figure illustrates the significant improvement of the suggested system in minimizing the required audio-cover signal. Finally, a number of tests are also performed to measure system robustness against various types of attack. The obtained results demonstrated system robustness against several bench mark attacks, as shown in Table 2. The used attacks are defined by Stirmark watermarking benchmark [12].

Figure 11. SNR versus minimum audio-cover period.The robustness against attacks is measured using the BER (Bit Error Rate) which is defined as the ratio of incorrect extracted bits to the total amount of embedded bits, as expressed as [13]:-----------------------------------------(6)where L is the watermark length, Wn corresponds to the nth bit of the original embedded watermark and W'n corresponds to the nth bit of the extracted watermark.

5. CONCLUSIONSThis paper presented novel extensions to a previously reported digital audio watermarking algorithm based on DWT and SVD techniques. The suggested extensions expanded the possibility of inserting more frames in the original audio signal and improved quality of the watermarked audio by changing the value of watermark intensity. Performance of the proposed enhancements was tested under different watermark sizes and audio periods. The obtained test results showed improved performance over the original algorithms in terms of audio signal quality (25% higher SNR), 69% reduction in the required minimum audio-cover period, and improved robustness against various watermark benchmark attacks.

REFERENCES

1. Y. Liu, H. S Yun, J. S Sung, N. S. Kim, "A novel audio fingerprinting scheme based on sub band envelop hashing", Proc. Asia-Pacific Signal and Information Processing Association, pp.813-816, Oct. 2009.2. A. Bouridane ,L. Ghouti ,M. Ibrahim and S. Boussakta Digital Image Watermarking Using Balanced Multiwavelets, IEEE Transactions on Signal Processing, Vol. 54, No. 4, pp. 1519- 1536, April 2006.3. S. Ramakrishnan, T. Gopalakrishnan, K. Balasamy, SVD Based Robust Digital Watermarking For Still Images Using Wavelet Transform, CCSEA 2011, CS & IT 02, pp. 155167, 2011.4. N. Lalitha, G. Suresh, V. Sailaja, Improved Audio Watermarking Using DWT-SVD, International Journal of Scientific & Engineering Research, Vol. 2, Issue 6, June, 2011,ISSN 2229- 5518.5. W-N Lie and L-C. Chang, Robust and High-Quality Time- Domain Audio Watermarking Based on Low-Frequency Amplitude Modification, IEEE Transactions on Multimedia, Vol. 8, No.1, February 2006.6. H. zer, B. Sankur, and N. Memon, An SVD Based Audio Watermarking Technique, ACM Workshop on Multimedia and Security, New York, August 1-2, 2005.7. A. Al-Haj and A. Mohammad, Digital Audio Watermarking Based on the Discrete Wavelets Transform and Singular Value Decomposition, European Journal of Scientific Research, ISSN 1450-216X Vol.39 No.1, pp.6-21, 2010.8. H. Andrews and C. Patterson, "Singular Value Decomposition (SVD) Image Coding", IEEE Trans. on Communications; 42(4): 425-432, 1976.9. A. Lang, Stirmark Benchmark for Audio (SMBA) [Online]:http://amsl-smb.cs.uni-magdeburg.de/smfa/ main. php, Accessed on December 13, 2011.10. J. Grody and L. Brutun,Performance Evaluation of Digital Audio Watermarking algorithms, Proc. of the 43rd IEEE Midwest Symposium on Circuits and Systems, 456-9, 2000.

Source codefunction varargout = gui_audioWatermark(varargin)%GUI_AUDIOWATERMARK M-file for gui_audioWatermark.figgui_Singleton = 1;gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @gui_audioWatermark_OpeningFcn, ... 'gui_OutputFcn', @gui_audioWatermark_OutputFcn, ... 'gui_LayoutFcn', [], ... 'gui_Callback', []);if nargin && ischar(varargin{1}) gui_State.gui_Callback = str2func(varargin{1});end if nargout [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});else gui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT % --- Executes just before gui_audioWatermark is made visible.function gui_audioWatermark_OpeningFcn(hObject, eventdata, handles, varargin)% This function has no output args, see OutputFcn.% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% varargin unrecognized PropertyName/PropertyValue pairs from the% command line (see VARARGIN) % Choose default command line output for gui_audioWatermarkhandles.output = hObject; handles.alpha = 0.1;handles.AudioInput = [];handles.Fs = 8000;handles.LogoHash = '';handles.key = [];handles.vm_idx = [];set(handles.hashIn,'string',' ') set(handles.pushbutton7,'enable','off','visible','off') set([handles.PlayAudio,handles.LoadLogo,handles.InsertWatermark],... 'Enable','inactive') cla(handles.InputAxis)cla(handles.OutputAxis)cla(handles.LogoAxis) set(handles.InputAxis,'xtick',[],'ytick',[])set(handles.OutputAxis,'xtick',[],'ytick',[])set(handles.LogoAxis,'xtick',[],'ytick',[]) set(handles.hashIn,'backgroundcolor',[1 1 1]) set(handles.InsertWatermark,'string','Insert Watermark')set(handles.LoadInput,'string','Load Input Audio')set(handles.PlayAudio,'string','Play Input Audio')set(handles.OutputAxis,'visible','on','xtick',[],'ytick',[])set(handles.LoadLogo,'visible','on')set(handles.PlayOutput,'visible','on')set(handles.LogoAxis,'visible','on','xtick',[],'ytick',[])set(handles.InsertWatermark,'Enable','inactive')set(handles.popupmenu1,'value',1) % Update handles structureguidata(hObject, handles); % UIWAIT makes gui_audioWatermark wait for user response (see UIRESUME)% uiwait(handles.figure1); % --- Outputs from this function are returned to the command line.function varargout = gui_audioWatermark_OutputFcn(hObject, eventdata, handles)% varargout cell array for returning output args (see VARARGOUT);% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA) % Get default command line output from handles structurevarargout{1} = handles.output; function hashIn_Callback(hObject, eventdata, handles)% hObject handle to hashIn (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of hashIn as text% str2double(get(hObject,'String')) returns contents of hashIn as a double % --- Executes during object creation, after setting all properties.function hashIn_CreateFcn(hObject, eventdata, handles)% hObject handle to hashIn (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called % Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor','white');end % --- Executes on button press in LoadInput.function LoadInput_Callback(hObject, eventdata, handles)% hObject handle to LoadInput (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)[handles.fn,pn] = uigetfile('*.wav');if handles.fn==0 return;endset(handles.hashIn,'string','')[handles.AudioInput, handles.Fs]= wavread([pn,handles.fn]); plot(zeros(size(handles.AudioInput(:,1))),'parent',handles.OutputAxis)plot(handles.AudioInput(:,1),'parent',handles.InputAxis) set(handles.InputAxis,'XLim',[0,size(handles.AudioInput,1)])set(handles.OutputAxis,'XLim',[0,size(handles.AudioInput,1)]) set(handles.InputAxis,'xtick',[],'ytick',[])set(handles.OutputAxis,'xtick',[],'ytick',[]) set(handles.PlayAudio,'Enable','on')set(handles.LoadLogo,'Enable','on')set(handles.hashIn,'backgroundcolor',[1 1 1]) % Update handles structureguidata(hObject, handles); % --- Executes on button press in PlayAudio.function PlayAudio_Callback(hObject, eventdata, handles)% hObject handle to PlayAudio (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)if ~isempty(daqfind) wavplay(handles.AudioInput(:,1),handles.Fs)end % --- Executes on button press in LoadLogo.function LoadLogo_Callback(hObject, eventdata, handles)% hObject handle to LoadLogo (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)cla(handles.LogoAxis)set(handles.hashIn,'backgroundcolor',[1 1 1],'string','') [fn,pn] = uigetfile('*.png;*.bmp;*.jpg;*.tif','Select the logo file');if fn==0 return;end set(handles.hashIn,'string','')Logo = imread([pn,fn]);handles.Logo = Logo;% Update handles structureguidata(hObject, handles); Hash = hash(Logo); HashDB = struct('OwnerName','','Hash','');if exist('HashDB.mat','file') load('HashDB.mat')end imshow(Logo,'parent',handles.LogoAxis)pause(1) OwnerName = '';for i = 1:numel(HashDB) if strcmpi(Hash,HashDB(i).Hash) if strcmpi(Hash,HashDB(i).Hash) OwnerName = HashDB(i).OwnerName; end endend if isempty(OwnerName) msgbox('Please Enter Owner Name to update the Hash Database', 'New Logo','warn') set(handles.hashIn,'string',OwnerName,... 'backgroundcolor',[1,1,0],... 'enable','on') set(handles.pushbutton7,'enable','on','visible','on') return;endset(handles.hashIn,'string',OwnerName,... 'backgroundcolor',[0.5,1,0],... 'enable','inactive')set(handles.pushbutton7,'enable','off','visible','off') handles.LogoHash = Hash; set(handles.InsertWatermark,'Enable','on') % Update handles structureguidata(hObject, handles); % --- Executes on selection change in popupmenu1.function popupmenu1_Callback(hObject, eventdata, handles)% hObject handle to popupmenu1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)if get(handles.popupmenu1,'value')==2 cla(handles.OutputAxis) cla(handles.LogoAxis) set(handles.hashIn,'string','','backgroundcolor','w') set(handles.InsertWatermark,'string','Extract Watermark') set(handles.LoadInput,'string','Load Audio') set(handles.PlayAudio,'string','Play Audio') set(handles.OutputAxis,'visible','off') set(handles.LoadLogo,'visible','off') set(handles.PlayOutput,'visible','off') set(handles.LogoAxis,'visible','off') set(handles.InsertWatermark,'Enable','on') set(handles.hashIn,'string','')else set(handles.InsertWatermark,'string','Insert Watermark') set(handles.LoadInput,'string','Load Input Audio') set(handles.PlayAudio,'string','Play Input Audio') set(handles.OutputAxis,'visible','on') set(handles.LoadLogo,'visible','on') set(handles.PlayOutput,'visible','on') set(handles.LogoAxis,'visible','on','xtick',[],'ytick',[]) set(handles.InsertWatermark,'Enable','inactive') set(handles.hashIn,'string','')end% Hints: contents = cellstr(get(hObject,'String')) returns popupmenu1 contents as cell array% contents{get(hObject,'Value')} returns selected item from popupmenu1 % --- Executes during object creation, after setting all properties.function popupmenu1_CreateFcn(hObject, eventdata, handles)% hObject handle to popupmenu1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called % Hint: popupmenu controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor','white');end % --- Executes on button press in InsertWatermark.function InsertWatermark_Callback(hObject, eventdata, handles)% hObject handle to InsertWatermark (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Frame length in time domain len_Frame_t = 800; % Count of frames per groupgroup_members = 30; if strcmpi(get(hObject,'string'),'Insert Watermark') % Prepare the watermark bits w = dec2bin(handles.LogoHash)-48; % FINDIN HOW MUCH OF THE SIGNAL IS NEEDED FOR THIS DATA len_w = numel(w) len_group = group_members*len_Frame_t; len_s = (len_w+1) * len_group; signal = handles.AudioInput(:,1); if len_s > numel(signal) msgbox('The selected audio signal is very short','!!!','warn') return end sig = signal(1:len_s); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % DATA EMBEDDING % A frame among the 30 frames in a group is selected % This frame is subjected to 4 level dwt % The coefficients such as A4,D4,D3,D2 and D1 are used to make a matrix. % SVD of this matrix is taken and the first element of the s-matrix is % subjected to the watermarking process:- % s11 = s11 + alpha*w(n) % where, % s11 = first element of s-matrix % w(n) = the watermark bit % alpha = watermark strength alpha = 0.1; % Process vm_idx = 31:30:len_s; [sig_w, key] = Audio_DataEmbedding(sig,w,alpha,len_Frame_t,vm_idx); handles.key = key; signal(1:len_s) = sig_w; fn = sprintf('%s_e.wav',handles.fn); wavwrite(signal,handles.Fs,32,fn); fn = sprintf('%s_k.mat',handles.fn(1:4)); save(fn,'key') handles.OutputAudio = signal; handles.AudioInput = signal; plot(signal,'parent',handles.OutputAxis) set(handles.OutputAxis,'XLim',[0,size(signal,1)]) set(handles.OutputAxis,'xtick',[],'ytick',[]) set(handles.PlayOutput,'Enable','on') handles.alpha = alpha; handles.vm_idx = vm_idx; guidata(hObject,handles)else signal = handles.AudioInput(:,1); if isempty(handles.key) fn = sprintf('%s_k.mat',handles.fn(1:4)); if exist(fn,'file') load(fn) end else key = handles.key; end alpha = handles.alpha; len_s = numel(key)*group_members*len_Frame_t; vm_idx = 31:30:len_s; W = Audio_DataExtracting(signal,key,alpha,len_Frame_t,vm_idx); bitsPerChar = 7; len_data_rx = numel(W); bits_rx = reshape(W,[len_data_rx/bitsPerChar,bitsPerChar]); ascii_rx = char(bits_rx+48); char_rx = bin2dec(ascii_rx); data_rx = char(char_rx)'; if ~exist('HashDB.mat','file') return end load('HashDB.mat') Owner = ''; for i= 1:numel(HashDB) if strcmpi(data_rx, HashDB(i).Hash) Owner = HashDB(i).OwnerName; end end set(handles.hashIn,'string',Owner,'enable','inactive') guidata(hObject,handles) end % Update handles structureguidata(hObject, handles); function hashOut_Callback(hObject, eventdata, handles)% hObject handle to hashOut (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of hashOut as text% str2double(get(hObject,'String')) returns contents of hashOut as a double % --- Executes during object creation, after setting all properties.function hashOut_CreateFcn(hObject, eventdata, handles)% hObject handle to hashOut (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called % Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor','white');end % --- Executes on button press in PlayOutput.function PlayOutput_Callback(hObject, eventdata, handles)% hObject handle to PlayOutput (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)wavplay(handles.OutputAudio,handles.Fs) % --- Executes on button press in pushbutton7.function pushbutton7_Callback(hObject, eventdata, handles)% hObject handle to pushbutton7 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)OwnerName = get(handles.hashIn,'string'); if isempty(OwnerName) msgbox('Please Enter Owner Name', 'Empty field !!!', 'warn') return;end Logo = handles.Logo; if exist('HashDB.mat','file') load('HashDB.mat')else HashDB = struct('OwnerName','','Hash','');end n = numel(HashDB);if isempty(HashDB(n).Hash) n = n-1;end n = n+1;HashDB(n).OwnerName = OwnerName; if isempty(HashDB(n).OwnerName) return;end Hash = hash(Logo); for i = 1:numel(HashDB) if strcmpi(Hash,HashDB(i).Hash) OwnerName0 = HashDB(i).OwnerName; if ~strcmpi(OwnerName0,HashDB(n).OwnerName) msgbox('Invalid Owner','!!!','error') return; end endend HashDB(n).Hash = Hash;save HashDB HashDBhandles.LogoHash = Hash; set(handles.pushbutton7,'enable','off','visible','off')set(handles.LoadLogo,'enable','inactive')set(handles.InsertWatermark,'enable','on') guidata(hObject,handles)hash.mfunction h = hash(inp)% HASH - Convert an input variable into a message digest using any of% several common hash algorithms%% USAGE: h = hash(inp)%% inp = input variable, of any of the following classes:% char, uint8, logical, double, single, int8, uint8,% int16, uint16, int32, uint32, int64, uint64% h = hash digest output, in hexadecimal notation inp=inp(:);% convert strings and logicals into uint8 formatif ischar(inp) || islogical(inp) inp=uint8(inp);else % convert everything else into uint8 format without loss of data inp=typecast(inp,'uint8');end % create hashx=java.security.MessageDigest.getInstance('SHA-1');x.update(inp);h=typecast(x.digest,'uint8');h=dec2hex(h)';if(size(h,1))==1 % remote possibility: all hash bytes < 128, so pad: h=[repmat('0',[1 size(h,2)]);h];endh=lower(h(:)');h=h(1:4);clear xreturnAudio_DataEmbedding.mfunction [sig_w, key] = Audio_DataEmbedding(sig,w,alpha,len_Frame_t,vm_idx)% AUDIO WATERMARKING % Initialization of the output signalsig_w = sig; % length of the input data bitstreamlen_w = numel(w); % Initialization of the key vectorkey = zeros(1,len_w); % Processfor n = 1:len_w %% DWT % [CA,CD] = DWT(X,'wname') computes the approximation % coefficients vector CA and detail coefficients vector CD, % obtained by a wavelet decomposition of the vector X. % 'wname' is a string containing the wavelet name. wname = 'db1'; start_idx = vm_idx(n)*len_Frame_t+1; finish_idx = start_idx+len_Frame_t-1; frame = sig(start_idx :finish_idx); % LEVEL 1 DWT [A1, D1]= dwt(frame',wname); % Length of the coefficient len_d1 = length(D1); % LEVEL 2 DWT [A2, D2]= dwt(A1,wname); % Length of the coefficient len_d2 = length(D2); % LEVEL 3 DWT [A3, D3]= dwt(A2,wname); % Length of the coefficient len_d3 = length(D3); % LEVEL 4 DWT [A4, D4]= dwt(A3,wname); % Length of the coefficient len_d4 = length(D4); len_a4 = length(A4);

%% MATRIX FORMATION Matrix = [A4 D4 D3 D2; D1]; %% SINGULAR VALUE DECOMPOSITION % SVD Singular value decomposition. % [U,S,V] = SVD(X) produces a diagonal matrix S, of the same % dimension as X and with nonnegative diagonal elements in % decreasing order, and unitary matrices U and V so that % X = U*S*V'. [u s v] = svd(Matrix); % extract the first element of the s-matrix s11 = s(1,1); key(n) = s11; % Embedding process s11w = s11 * (1 + alpha*w(n)); % Replace the first element of s-matrix with the embedded element s(1,1) = s11w; % INVERSE SINDULAR VALUE DECOMPOSITION Matrix_w = u*s*v'; %% DECOMPOSITIION OF THE MATRIX INTO THE COEFFICIENTS start_A4 = 1; finish_A4 = len_a4; A4_w = Matrix_w(1,start_A4:finish_A4); start_D4 = len_a4+1; finish_D4 = len_a4+len_d4; D4_w = Matrix_w(1,start_D4:finish_D4); start_D3 = len_a4+len_d4+1; finish_D3 = len_a4+len_d4+len_d3; D3_w = Matrix_w(1,start_D3:finish_D3); start_D2 = len_a4+len_d4+len_d3+1; finish_D2 = len_a4+len_d4+len_d3+len_d2; D2_w = Matrix_w(1,start_D2:finish_D2); start_D1 = 2; finish_D1 = len_d1; D1_w = Matrix_w(2,1:len_d1); %% INVERSE DWT 4 LEVEL A3_w = idwt(A4_w,D4_w,wname); A2_w = idwt(A3_w,D3_w,wname); A1_w = idwt(A2_w,D2_w,wname); frame_w = idwt(A1_w,D1_w,wname); sig_w(start_idx:finish_idx) = frame_w; end Audio_DataExtraction.mfunction W = Audio_DataExtracting(sig_w,key,alpha,len_Frame_t,vm_idx)% AUDIO WATERMARK EXTRACTING % Length of the keylen_k = numel(key); % Initialization of the output bitstream vectorW = zeros(1,len_k); % Processfor n = 1:len_k %% DWT % [CA,CD] = DWT(X,'wname') computes the approximation % coefficients vector CA and detail coefficients vector CD, % obtained by a wavelet decomposition of the vector X. % 'wname' is a string containing the wavelet name. wname = 'db1'; start_idx = vm_idx(n)*len_Frame_t+1; finish_idx = start_idx+len_Frame_t-1; frame = sig_w(start_idx :finish_idx,1); % LEVEL 1 DWT [A1, D1]= dwt(frame',wname); % Length of the coefficient len_d1 = length(D1); % LEVEL 2 DWT [A2, D2]= dwt(A1,wname); % Length of the coefficient len_d2 = length(D2); % LEVEL 3 DWT [A3, D3]= dwt(A2,wname); % Length of the coefficient len_d3 = length(D3); % LEVEL 4 DWT [A4, D4]= dwt(A3,wname); % Length of the coefficient len_d4 = length(D4); len_a4 = length(A4); %% MATRIX FORMATION Matrix = [A4 D4 D3 D2; D1]; %% SINGULAR VALUE DECOMPOSITION % SVD Singular value decomposition. % [U,S,V] = SVD(X) produces a diagonal matrix S, of the same % dimension as X and with nonnegative diagonal elements in % decreasing order, and unitary matrices U and V so that % X = U*S*V'. [u s v] = svd(Matrix); % extract the first element of the s-matrix s11w = s(1,1); s11 = key(n); % Extraction process s11 = round((s11w/s11 - 1)/alpha); W(n) = s11; end

HashDB_Updater.mclose all;clear all;clc [fn,pn] = uigetfile('*.jpg;*.png;*.bmp;*.tif','Select the logo file');Logo = imread([pn,fn]); if exist('HashDB.mat','file') load('HashDB.mat')else HashDB = struct('OwnerName','','Hash','');end n = numel(HashDB);if isempty(HashDB(n).Hash) n = n-1;end n = n+1;HashDB(n).OwnerName = input('Input the name of the Owner','s'); if isempty(HashDB(n).OwnerName) return;end Hash = hash(Logo); for i = 1:numel(HashDB) if strcmpi(Hash,HashDB(i).Hash) OwnerName0 = HashDB(i).OwnerName; if ~strcmpi(OwnerName0,HashDB(n).OwnerName) disp('Invalid Owner') return; end endend HashDB(n).Hash = Hash;save HashDB HashDB

HARDWARE CONFIGURATION

The printed circuit board (PCB) provides the electrical interconnections between various components and as well as provides mechanical support to the components. The components are soldered to the PCB. The quality of soldering directly affects the reliability of the circuit. The procedure for fabricating the PCB for any general project is described below.The printed circuit board consist the following steps.1. Lay out preparation2. Artwork Preparation3. Film Master Production4. Pattern transfer5. Etching6. Drilling

LAYOUT PREPARATIONThe layout is commonly prepared in the scale of 2:1. It offered a reasonable compromise below accuracy gained and handling convenience 2:1 artwork as the actual PCB area. Grid systems are commonly used for preparing the layout. The use of the grid sheet gives more convenience in placement of components and conductors. The grid system based on 0.1 is found to be too coursing, a grid equidistant of 0.025 or even 0.1 mm is recommended. Procedure1. Each and every PCB layout is viewed from component side.2. The designing of the layout is started with an absolutely clear component list and circuit diagram is available.3. The larger component are placed first and the space in between is filled with area4. In the designing of the PCB layout, It is very importance to divide the circuit in to functional sub units. Each of these sub units are realized in the defined the portion of the board.5. The components are placed in the grid sheet tanning the standard length and width.6. The punched lay out is circled to taking the standard size of the land pads.7. These pads are entering connected as the circuit diagram.8. The mirror image of these gives the solder side of the PCB. PATTERN TRANSFER After the film is processed the film master are obtained. The transfer of the conductor which on film master on to the copper clad base material is done by two methods mainly photo printing and screen printing. Photo printing is extremely accurate process which is also applied to the fabrication of semi-conductors. Screen printing is comparatively cheap and simple method for transfer although less precise then photo printing. But this is less costly, this method is commonly used. SCREEN PRINTINGIn screen printing, the process is very simply. A screen fabric with uniform meshes and opening is stretched and fixed on a solid frame of metal or wood. The circuit pattern is photographically transferred on to screen, leaving the meshes in the rest of area as closed. In the actual printing step ink is forced by moving queue through the open master on to the surface of the material to be printed. The light sensitive material is coated on to the screen and using film master the pattern is transferred to the screen. The using ink and the pattern is transferred to the copper clad sheet.Two methods are used for screen printing into screen 1. Direct method2. Indirect method.In direct method than photographically sensitive emulsions are used for transferring patterns. The Wet material is uniformly coated to the screen and then exposed. In indirect method, the photographically sensitive film is transferred to screen. The film is exposed and ten it sticker in to the screen. The pattern is then transferred to the screen using the links and squeegee.ETCHINGThe removal of unwanted copper from the copper clad sheet is known as etching. For this 4 types of tanks are used.1. Ferric chloride 2. Cupric chloride3. Chromic acid4. Alkaline ammoniaAmong these ferric chloride is cheap and popular etchant is ferric chloride and also suited for home and industrial applications. The high corrosive powers of ferric chloride lead to shot etching time and little under etching. Ferric chloride matches well photo and screen printed resists

DRILLINGDrilling of component mounting holes in to PCBs is by the most important mechanical machining operation PCB production process. The importance of the whole drilling on PCB has further group with electronic component miniaturization and its need for smaller whole diameters and higher package density where whole purchasing is practically routed out. Four types of drilling are commonly used 1. Drilling by direct sight.2. Drilling by optical slight.3. Jig drilling.4. NC drilling.

COMPONENT MOUNTINGComponents are basically mounted on one side of the board. On polarized two lead components are mounted to give the marking or orientation throughout the board. The component orientation can be both Horizontal as well as vertical but uniformly, directions are placed. The Uniformity in orientation of polarizes components is determining during design of PCB.Some recommended mounting techniques are given below Horizontally mounted resister must touch the board resister to avoid lifting of solder along with the copper pattern under pressure on the resister body Vertical mounted resister should not be flash to board surface to avoid the Strain on the solder joint as well as the component need to junction due to Different thermal expansion coefficient of lead board material also where necessary spaces should be provided. Coated or sealed components have to be mounting such a way as to provide a certain distance from the board. When jumper wires cross over the conductors, jumper wire must be insulated. Transistors mounting should be never done flash to be board. This could give considerable stress on the solder joints and to the lead connection beside the possible over heating during the soldering operations.

SOLDERING Soldering is an important process in assembling electronic products. Solder joints are formed by nature of the welding process. Solder does not stick on the insulating surface. on most metal wetting will take place and a joint will form if the work piece and solder are not enough and the surface are clean and free from oxides . The surface to be soldered must be sufficiently not to permit wetting by the solder. The component to be soldered should not be damaged by heating. The metal surface to be wetted must have good wet ability. They must be clean so that metallic contact can be established between older and metal. For good soldering select proper rating of soldering iron and select proper tip. Pick up the [proper solder wire commonly 60:40 tin and led composition are used. Make a good contact between the soldering tip and the part to be soldered. Apply small amount of flux and make a contact between the soldering iron and joint till good spreading of soldering of soldering has been realized.

TESTING AND ASSEMBLYAssembly consists of soldering of components and wires on the PCB and mechanical of wired PCB and other assemblies. Testing is carried out even at design phase itself in breadboard level to verify the design, so that little circuit changes are required after designing the PCB.TESTING

After soldering the components on to the PCB, the board is thoroughly cleaned for any residual flux and wire leads. All the components are checked for their value and for the proper orientation if applicable. Before ICs are inserted into the sockets, power applied to the board and voltages are measured at the IC power point. Power is switched off before the ICs are inserted. Press the required switch and check whether the corresponding code is available at various stages (Receiver, display and the motor driver input.). If all these requirements are satisfied connect the required appliance in the circuit.ASSEMBLYThe tested Pcb is mounted on the mechanical structure. The mechanical structure is constructed using PVC foam sheet. The ultrasonic transmitter receiver module is mounted on the side of the structure such that the sound waves transmitted can easily be received. The indicators are also made easily visible.

PASSWORD BASED DOOR LOCKING SYSTEMAIMNowadays every devices operation is based on digital technology. For instance, token-based digital identity devices, Fort-token mobile and digital-based door lock systems forauto door opening or closingare all based on digital technology. These locking systems are used to control the movement of door and are functional without requiring a key to lock or unlock the door. These locking systems are controlled by a keypad and are installed at the side hedge of the door.In this project, a keypad is attached to the door for opening and closing operations of the door. After entering the 4bit code, if that code matches with the predefined one, then the door will unlock for a limited period of time. After prolonging the unlocking for a fixed period of time, the relay reenergizes and the door gets locked again. If anyone enters a wrong code in an attempt to open the door and attempts thrice, then this system immediately switches an alarm or a buzzer.BLOCK DIAGRAM

Power SupplyMotor Driver8051 Micro Controller

LCD

Motor

BuzzerKeypad

The operation of this system can be described by the above block diagram, which consists of blocks as keypad, a buzzer, an LCD, a Motor Driver and a motor. The Keypad is an input device that helps to enter a code to open the door. This block gives the entered code signals to the microcontroller. The buzzer and LCD are the final indicating devices for displaying the information and alarming. The motor moves the door: opens and closes the door, and the motor driver drives this motor by receiving control signals from the microcontroller.Themicrocontroller used in this projectis from 8051 family, and it is programmed with the Keil software. When a person enters a password by using various keys in the keypad ranging from 0 to 9 including Enter and Escape keys, then the microcontroller immediately reads the data and compares it with the stored data.If this data matches, the microcontroller sends display information to the LCD display as Code is authenticated. Furthermore, the microcontroller sends the command signals to the motor-driver IC to rotate the motor in a particular direction such that the door opens. After sometime, the spring system with a specified time delay closes its relay, and then the door starts closing and slowly comes to its normal closed position.If the person attempting to open the door enters a wrong password, then the microcontroller switches the alarm for further course of action. In this way, a simple door-lock system can be implemented with the use of a microcontroller.CIRCUIT DIAGRAM

PCB LAYOUT

RESULTThe project Password Based Door Locking System was successfully designed and tested. It was found to function as per the expectations.

SPY ROBOTAIMTo develop a robot used to explore a remote location by mapping the path with the help of a server and sensing the obstacles with IR sensor and transmits the collected data to the control station using wireless means.BLOCK DIAGRAMThis project develops a running robot used to explore a remote location by mapping the path with the help of a server and sensing the obstacles with IR sensor and transmits the collected data to the control station using wireless means. This project consists of a microcontroller section and mechanical section. The microcontroller section stores a program that controls the movements of the robot, and object/obstacle detection. The mechanical section consists of DC motors for the movements of robot. The server helps in tracing the path of the robot. A robot is a mechanical device, a manipulator designed to perform many different tasks and capable of repeated, variable programming. To perform its assigned tasks, the robot moves parts, objects, tools, and special devices by means of programmed motions and points. The science and technology that deals with study of robots, their design, manufacture, and application is known as Robotics. Although the appearance and capabilities of robots vary vastly, all robots share the features of a mechanical, movable structure under some form of autonomous control. The control of a robot involves three distinct phases - perception, processing and action.The robot holds a mechanical structure that consisting servo motors for the movements of robot, and an electronic circuitry which acts as the CPU/ head (Intelligence) of the robot. A microcontroller acts as a Central Processing Unit, which stores an algorithm that controls the movements of the robot; ambient parameter sensing and object/obstacle detection. The robot is fixed with various sensors that monitor atmospheric temperature, light intensity, relative humidity and pressure. The object is detected using IR Sensor module which comprise of an IR transmitter and receiver section. If the distance to the object from robot is found less than the predefined value, the Sensor produces control signals to the CPU that changes the motion algorithm that matches to the situation and changes the path of the robot. The raw analog outputs from sensors after filtering and signal processing are directed to the ADC (Analog to Digital Converter) module. The digital output of the ADC further processing is given to the USART (Universal Synchronous Asynchronous Receiver Transmitter) module for communication purpose. The results are automatically archived on each time interval. A DC motor is like a light bulb; it has no electronics of its own and it requires a large amount of drive current to be supplied to it. This is the function of the L293D chips on the Handy Board, to act as large current switches for operating DC motorsThe control station interfaced with a wireless communication module interprets the incoming data from the microcontroller transmitted via ZIGBEE, and displays the needed data in corresponding manner. We can develop application software using MATLAB to achieve Control Station and Robot interfacing.Transmitter Section

Zigbee ModulePC with MATLAB

Receiver Section

AVRPower SupplyZigbee ModuleMotor Driver 1Motor Driver 2Motor 2Motor 1

IR Sensor

CIRCUIT DIAGRAM

PCB LAYOUT

RESULT

The project Spy Robot was successfully designed and tested. It was found to function as per the expectations.

Dept. of ECE5 VVIT