ISSN: 2278 909X International Journal of Advanced Research in …ijarece.org/wp-content/uploads/2016/05/IJARECE-VOL-5... · 2016-05-06 · Edge Detection Edge detection is an important

ISSN: 2278 – 909X International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)

Volume 5, Issue 4, April 2016

1109

All Rights Reserved © 2016 IJARECE

DESIGN OF X-RAY IMAGE PROCESSING

USING LABVIEW Meenal Bhatia

1 ,Swati .R.Dixit

2

1. M.Tech student, Department of Electronics and Telecommunication, G.H.Raisoni College Of Engineering and

Technology, Maharashtra, India

2. Research Scholar, Department of Electronics and Telecommunication, G.H.Raisoni College Of Engineering and

Technology, Maharashtra, India

Abstract— The Medical X-Ray imaging has grown widely

nowdays as a new research in image processing. Sometimes in

orthopaedic hospitals a doctor misses a fracture after going

through many X-Ray images. Hence computer detection for

fractures comes into role which can help a doctor for closer

inspection. For fracture detection, X-Ray images are used to

detect a fracture in bone. X-ray images are found to be very

noisy, hence it is very difficult to distinguish edges from the bone.

Therefore edge detection plays an important role in finding out

fracture. The proposed work uses X-Ray images for processing

and finding out detection of fracture using LabVIEW software.

Edges of the X-Ray image is found using canny edge operator.

Canny edge operator is found to be the best operator suitable for

detecting edges in an X-ray images. After the canny edge

detection, a contour analysis technique is used to find out the

fracture. For image acquisition, LabVIEW software is used. The

hardware implementation is done using National instrument

product SB-RIO 9631 board which has Xilinx Spartan 3

FPGA.FPGA with image processing is used for high speed

processing of images. LabVIEW offers a graphical coding which

is useful for interactive applications, hardware implementation

and real time applications. The combination of LabVIEW FPGA

module gives a new approach of using FPGA without writing

code in VHDL .Using LabVIEW FPGA, the code can be made in

blocks of LabVIEW and FPGA synthesizes that code. The work

below uses LabVIEW 14.0 and FPGA 14.0.

Index Terms—Edge detection, Canny operator, LabVIEW 14.0,

FPGA

I. Introduction

In recent years, medical imaging has gain a wider acceptance

in diagnosis of fractured image. This has given a new direction

in the field of medical imaging which collects qualitative

information of the images to study physiology of patients. So

automatic diagnosis has become easier with the help of

computer processing abilities. X-Ray is the oldest method to

determine the bone shape. The X-Ray images helps the

medical practitioners for understanding the X-Ray image

which will help them in decision-making .A bone X-Ray can

be of hand, chest, wrist, elbow, shoulder etc of injuries.

Fracture occurs when the bone is not able to hold out forces.

Sometimes a radiologist is unable to read X-Ray images. It

may be due to light conditions. So fractures are not seen by

naked eyes. Hence to improve diagnosis, the images are

analyzed using medical image processing which helps

physicians in making decision efficiently. However to achieve

this, as there are variations of bone structure, different

lightning conditions, different visual characteristics and

different noises present in X-Ray images. Fracture detection of

X-Ray image is still not explored. There are very few studies

focused on fracture detection of X-Ray images. Now also X-

Ray inferences relies on human .Hence different doctors

reading the same X-Ray film can give different conclusions.

Hence computer image processing technology can proved to

be beneficial to detect fracture which can help to improve

doctors efficiency for reading X-Ray images. Hence it may

also save the time of the doctor required for understanding X-

Ray image

In this paper, a method is used to automatically detect

fractures in X-Ray image. X-Ray images are larger in size of

1024 x 1024 size, hence images are reduced to 800 x 800

pixels. For edge detection, a canny operator is used. Then for

fracture detection, a contour analysis technique is used in

LabVIEW. The result are shown in front panel of the

LabVIEW.

II. Design Methodology

Fig 1.Proposed Model



1110


X-Ray Image:

The first stage is input image in LabVIEW which is the

X-Ray image. X-Ray creates an image of a bone on the X-

Ray film and a bone crack is the fracture. The X-Ray images are larger in size and its resolution was 1024 x 1024.The X-

Ray images resolution is reduced in the 800 x 800 pixel.

Color Plane Extraction:

After acquiring X-Ray image, next process is color plane extraction. X-Ray images are stored in the format of RGB,

hence there is a need to do grayscale conversion[11]. After

using this block the image is converted to 8 bit grayscale

image.

Math Look Up Table

Math lookup table is used for applying brightness and contrast

in images. The contrast and the brightness is improvised here.

The block converts the pixel value of the original image by

taking the new pixel values. The Look up table consist of

mathematical curves which enhances and changes the pixel

value in image. Look up table includes functions like

exponential, square, power etc. Here a mathematical square

function is used in image to improve the brightness and the

contrast.

Edge Detection

Edge detection is an important tool which aims in identifying

transition in image where brightness changes sharply. An edge

is the boundary between an object and background. Canny

edge detection is an operator used mostly for detecting edges

in X-Ray images. This algorithm consist of following steps:

Smoothening, finding gradient, non-maximum suppression and

thresholding .The following are the steps for canny edge

operator:

1.)Smoothen the image by applying Gaussian filter on the

image. The noise can be considered as an edge if a Gaussian

filter is not applied..

2.)Find the edges by doing horizontal and vertical searching by

applying operators like Sobel , Robert, Prewitt etc.

The following is sample of Sobel operator

H(x) = −1 0 1−2 0 2−1 0 1

………..(1)

H(y) = −1 −2 −1 0 0 0 1 2 1

………..(2)

4.)Determine the direction of edge using the following formula

GM(x,y)= 22 HyHx - - - - - - - - (3)

5.)Canny edge detection has two thresholds(maximum and

minimum threshold).A pixel is considered as an edge if found

to be greater than the maximum threshold. The pixel which are

less than minimum threshold are filtered out. A pixel for edge

is accepted only if it lies between the maximum and minimum

threshold and is connected to one of the pixel whose value is greater than maximum threshold .

6.)Non-maximum suppression gives a slimmer line edge.

7.)Canny edge detection is advantageous because it finds out

errors due to smoothing concept. A good signal to noise ratio

is achieved because of non maximum suppression .The edges

are also detected clearly due to double threshold method. The

disadvantage is this that the time consumption is more

Gray Morphology Gray-scale morphology is used for enhancing or removing

bright pixels. Gray scale morphology have different operations

like dilation and erosion, opening, and closing operations.

Here dilation is used, which enhance the bone part edges of

brighter pixels. In dilation each pixel becomes equal to

maximum value its neighbor pixel.

Contour Analysis

After applying gray morphology on image in LabVIEW ,the

next method is contour analysis technique which helps to find

out the cracked detected parts of bone. In contour analysis curves are extracted from the edge. Curve is nothing but a set

of points. A connected curve is represented as a contour. The

point for selecting a curve is determined by a seed point. The

seed point is found by selecting a point where edge is greater

than edge threshold. An edge threshold selected here is 75.This

is a seed point when a curve begin. The curve can be straight

line curve a circle or a closed contour etc. These curves are

then plotted on X-Y graph plot. A distance is computed from

this contour. The length of a digital contour can be obtained by

adding all the co-ordinate points. It is seen that a small

distance is computed, if the fracture is found and a red line

contour is seen in the image showing the fracture location. Applying this analysis on many images of X-Ray, it is found

that if the computed distance is found to be less than 1,than a

fracture is not detected and its result is displayed on front

panel. And if a large contour is obtained, then its distance is

found to be greater than 1 and a fracture detected will be

shown in indicator on the front panel. It also shows location of

fracture represented by a red line.

III. LABVIEW CODING

The LabVIEW coding is shown below in fig 2.Where first an

image is acquired from database available in PC.Then a Gray-

scale conversion is followed by applying some brightness and

contrast in the image. Then edges are found in the image. A



1111


contour analysis is applied to extract the curves and distance is

computed from the graph of x-y plot. Finally a comparator is

used to find out the fracture detected or not and the result is

displayed on front panel of the LabVIEW.

Fig 2. LabVIEW Code

IV. Hardware Implementation

Software has become less useful in image processing now

days, as image size and bit depths grows larger. FPGA are

used for high speed processing in image, video. With the

development of FPGA, a large amount of data are captured

using satellite and ground based detection systems. The

Labview platform consist of NI SINGLE BOARD RIO

9631.Single board rio is a product from national instruments

which has XILINX Spartan 3 FPGA in it. It also consist of a

microprocessor which is from Freescale Semiconductor. It also

has analog i/o and digital i/o.

Fig 3.SB-RIO 9631

Programming with FPGA

The LabVIEW FPGA Module gives a new direction in the

field of FPGA ,by using graphical coding on NI

Reconfigurable I/O (RIO) ,which are the FPGA hardware

targets. For FPGA implementation FPGA VI and Host VI is

required .

Project Explorer

The project explorer window shows different parts that a

LabVIEW project constitutes. An addition of VI’s can be done

here. The Project Explorer shows the FPGA target which

specifies the FPGA board, real time VI or also called as host

VI and the FPGA VI. The FPGA target runs on FPGA VI



1112


Fig.4 Project explorer window

FPGA VI

Fig.5 FPGA VI

HOST VI

Fig.6 HOST VI



1113


V. Code Compilation

FPGA VI is compiled and FPGA compilation report is

obtained.During compilation, the graphical design is converted into

bitfiles.After successful compilation, the results are shown on front

panel of LabVIEW.

Fig.7 Compilation Report

VI. Results

Different X-ray images are used which consist of fractured and

Non-fractured images shown in fig 8(a),8(b),8(c),8(d).8(e) and

shows the output on front panel .Fig 9 shows the accuracy of

the proposed system.It is found to be 96.09%.Fig.10 shows

the processing time for various X-Ray images.The average

time is found to be 2.06743 sec .

Fig.8(a) “Fracture Found”

Fig.8(b) “Fracture Not Found”

Fig.8(c) “Fracture Not Found”

Fig.8(d) “Fracture Found”

Fig.8(e) “Fracture Found”



1114


Fig.9 Accuracy of the proposed system

Fig.11 Processing time for different X-Ray images

VII. Conclusion

The paper describes the processing of X-Ray images

using a LabVIEW platform.It uses canny operator for

edge detection of X-Ray images. LabVIEW platform

involves simple graphical coding for detecting fractures.

The implementation of LabVIEW with FPGA gives a

high speed processing in images. It also gives a platform

to use FPGA without the knowledge of VHDL. This

design is able to locate the fracture in a bone X-Ray

images successfully with the help of LabVIEW. This

system is able to give the best accuracy as compared to

previous works. This design is able to reduce the

processing time. The preliminary results are presented

which shows fracture detection of X-Ray images .

VIII. References

[1] Subodh Kumar,Prabat Pandey“Implementation of X-Ray Image Segmentation by Using Edge Detection Based On Sobel Edge Operator”(International Journal of innovative research and study,feb 2014 ,vol 3 issue2)

[2] Madhulika,DivakarYadav,Madhurima,Pritee Gupta,Gurpreet Kaur ,Jyoti Mallika Gandhi,Ajeet Singh “Implementing Edge Detection for Medical Diagnosis of a Bone in Matlab” (International Journal of Computer Science and Information Technologies, Vol. 6 (2), 2015)

[3] Kuldeepak,Monika kaushik,Munish Vashishath,”License Plate Recognition System based on Image Processing Using Labview”(International Journal of Electronics Communication and Computer Technology (IJECCT),Volume 2 Issue 4 (July 2012).

[4] Ravi kumar A.V,Dr Nataraj K .R,Dr Rekha K.R, “Morphological real time video edge detection using LabVIEW”( International Journal of Computer Science and Information Technologies, Vol. 3 (2) , 2012,3808-3811)

[5] Kumar A.V, Nataraj K.R “ Result Analysis of LabVIEW and MatLab in Application of Image Edge Detection”(International Journal of Computer Applications (0975 – 888) Volume 48– No.9, June 2012)

[6] Swathika.B,Anandhanarayanan,Baskaran.B, and Govindaraj.R“Radius Bone Fracture Detection Using Morphological Gradient Based Image Segmentation

Technique”(International Journal of Computer Science and Information Technologies, Vol. 6 (2) ,2015)

[7] Shubhangi D.C, Raghavendra S.Chinchansoor, P.S Hiremath “Edge Detection of Femur Bones in X-ray images– A comparative study of Edge Detectors”( International Journal of Computer Applications (0975 – 8887 Volume 42– No.2, March 2012)

[8] Shubhada Gadgil , Dharmesh Verma,Dr. Meena S. Panse , Dr. Kushal Tuckley “Sea state monitoring hf radar controller using reconfigurable labview fpga”( 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies)

[9] Kazakova, N. Margala, M. Durdle, N.G. Mitra, “Sobel edge detection processor for a real-time volume rendering system”, Proceedings of the 2004 International Symposium on Circuits and Systems, 2004. ISCAS '04. Volume: 2

Publication Year: 2004 , Page(s): II - 913-16)

[10] Jincheng Wu, Jingrui Sun, Weying Liu, “Design and Implementation of Video Image edge Detection System Based on FPGA”, International conference on Image and signal Processsing 2010)

[11] Meenal Bhatia,Swati.R.Dixit “Edge detection for X-Ray image using Labview”,International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE ), Volume 5, Issue 3, (March 2016), e-ISSN: 2278 – 1021, p-ISSN No : 2319 – 5940.

Documents

ISSN: 2278 909X International Journal of Advanced Research in …ijarece.org/wp-content/uploads/2016/05/IJARECE-VOL-5... · 2016-05-06 · Edge Detection Edge detection is an important