INTRODUCTION

• Gestures include movements of hands, arms, face , head , and / or body.• They play a major role during communication by providing easier understanding.• Gesture Recognition is the technology that interprets human gestures via

mathematical algorithms.• The goal of Gesture Recognition is to provide an interaction between human body

with computer .• Human Machine Interface (HMI) refers to the relation between the human and the

computer.• Tracking of hand can be interfaced for controlling appliances through hand gesture

as a remote control device and prove to be a possible solution to control multiple gadgets.

• It can be very useful for physically challenged and blind people. • Two characteristics to be focused on

• Functionality• Usability

Figure: Gestures which will be usedSource: www.expatree.com

INTRODUCTION

• Home automation is a method for centralized control of different domestic electronic appliances .

• It can be achieved with embedded computing power and memory within dozens of household appliances.

• By utilizing devices according to the strict requirements, this technology is• Energy Efficient • Cost effective• Convenient

• We aim to operate home appliances like television sets,

lights, laptops , and fans by gestures without

the usage of a glove.

Source : Living Lab , www.fraunhofer.de

ABSTRACT

• Controlling home appliances and electronics gadgets through an infrared remote control is now general.

• Primary motive of proposing the new system of hand gesture remote control is– to remove the need to look for the hand held remote or reach to places where

the switches are located.– to create a natural interaction between human and computer where the

recognized gestures can be used for controlling an equipment.• The proposed project is targeted to implement a centralized home automation

system by integrating image processing techniques for Gesture recognition under human computer interaction with minimal hardware and optimized cost .

• It finds itself as a useful application for physically challenged and blind people.

LITERATURE SURVEY

To successfully implement the proposed project we have taken into account the existing

work done related to the project.

Aspects of image processing associated with gesture recognition

1. Image Enhancement

2. Image Restoration

3. Image Segmentation

In the papers referred so far, the following algorithms were used.• Pixel count• Detection of circles• Scanning method• Morphological operations • Edge detection

• Median and weiner filter• Threshold method

Pixel Count Algorithm [1]• Input image (RGB) is converted into Binary (BW)• Skin region is white (1) pixels and background is black(0)• Count the number of white pixels and check the range • Ranges are predefined to find the number of fingers raised• Invariant to rotation of hand• Size variant

Detection of circles[1]• Fingers are marked with black circles• RGB to BW• Black circles are represented as black in the white skin region • Number of circular objects are detected • Size and rotation Invariant • Circle on thumb may be miscalculated

Figure 1: Expected result

Figure 2: Expected result

Morphological Operation [1][2] [4]• RGB to BW• In paper [1], Binary image is filtered using median filter of suitable dimension.

It is eroded and further dilated to remove rough edges . This preprocessing is done to enhance the skin region .

• Hit or miss transformation is carried to recognize the pattern .• This transform recognizes the pattern of first structural element by deleting the

pattern of second structural element. • Dotted image is dilated and the solid closed object is counted• Pattern is specified by 2 structural elements SE1 and SE2• For this algorithm, the two structuring elements should be

SE1= [01] and SE2=[10]. • SE1 ∩ SE2 = Ф

• Invariant to both rotation and size of image• In paper [2] , it is used with segmentation to extract

Angle. Dilated with Gaussian LPF and eroded with larger radius disk.

Since the thumb line is always closest to the centroid and is the deciding factor for angle measurement, it is retained.

Figure 3: Expected result

Scanning method[1]• Robust• RGB to BW• Binary image is preprocessed with a median filter of suitable dimension • Erosion and dilation morphological operations are performed • Image is divided into 2 halves • Lower half contains thumb and Upper half contains remaining fingers• Left and right halves vertically • Horizontal and vertical scans are performed in both halves • Comparison is done after both the scanning and number of fingers are counted

Figure 1: Expected result Figure 1: Expected result

SR.NO METHODS ADVANTAGES LIMITATIONS

1 Pixel count Invariant to rotation Size variant

2 Detection of circles Independent of size and rotation

Circles miscalculated

3 MorphologicalOperations

Invariant to rotation and size of hand

Efficient only when background noise free

4 Scanning -Robust -Takes optimum operation time.

Complex computation

5 Edge detection Less sensitive to noiseRemoves stricking problems

-complex computation-time consuming

6 Median filtering No reduction in contrastDoes not shift boundary

Cannot distinguish between noise and fine detail removes both

PROBLEM STATEMENT

• To analyze , assess and there by determine an appropriate image processing algorithm for gesture recognition and implement the same for controlling multiple devices for energy-efficient home automation.

• The vision behind the project is to put forth a practical, commercially feasible and easily implementable home automation system that puts the entire control in the hands of the end user, literally.

SYSTEM DESCRIPTION

Hardware description Web cam Microcontroller RS232/ USB to TTL converter Voltage Regulator Relay driver LCD 16X2

• Hardware module accepts the control signal or data packet from the software module

through an interface and drives the actual components to action. • Serial communication is used to connect two devices.• The data packet undergoes level shifter to make the output from computational device

compatible with on board hardware .• Then it is fed to the Microcontroller which selects the desired device to be switched ON or

OFF. [3]• Each appliance that has to be controlled has a relay controlling circuit

BLOCK DIAGRAM

The given block diagram depicts the control of devices by the implementation of a gesture recognition system.

16 CHARACTER * 2 LINE LCD

RELAY DRIVER

LAMP

PUMP

Micro-controller

USB TO TTL

LAPTOP

Figure : Block Diagram

REFERENCES

[1] P Raghu Veera Chowdary, M Nagendra Babu, Thadigotla Venkata Subbareddy,Bommepalli Madhava Reddy, V Elamaran “Image Processing Algorithms for Gesture Recognition using MATLAB “ , Proc. Of IEEE International Conference on Advanced Communication Control and Computing Technologies ,2014

[2] Nagaraj N Bhat , ” Real Time Robust Hand Gesture Recognition and Visual Servoing “ , Proc. Of Annual IEEE India Conference (INDICON) 2012

[3] Khizir Mahmud , “Real Time Gesture Recognition and Processing to Control Television Set by Hand Beacon “ , IEEE Global High Tech Congress on Electronics(GHTCE), 2013

[4] A. Sharmila Konwar, B. Sagarika Borah, C. Dr.T.Tuithung “ An American Sign Language Detection System using HSV Color Model and Edge Detection “ , Proc. Of IEEE International Conference on Communications and Signal Processing (ICCSP), 2014

[5] V.Radha and M.Krishnaveni , Department of Computer Science, India,”Threshold based Segmentation using median filter for Sign language recognition system”.