INTERNATIONAL JOURNAL FOR RESEARCH & DEVELOPMENT IN

TECHNOLOGY Volume-5,Issue-5 (May-16)

ISSN (O) :- 2349-3585

All rights reserved by www.ijrdt.org

56

LABVIEW DESIGN FOR EDGE DETECTION USING

LOG GABOR FILTER FOR DISEASE DETECTION __________________________________________________________________________________________

Vipul Kumbhalwar1, Swati Dixit

2

12M.Tech student, Department of Electronics and Telecommunication,

12M.Tech student, G.H.Raisoni College Of Engineering and Technology, Maharashtra, India.

Abstract –Edge detection is an important tool in the field of

image processing, Disease like tonsillitis, tumor, fracture

and many more can be detect and cured in its early stage, by

detecting the edges of that disease, so edge detection having

always given first attention in the field of image processing.

In this paper tonsillitis detection module is design in

LabVIEW and then it implemented on NI Sbrio 9631 FPGA

kit. The algorithm used is SOBEL operator and for best

ridges and fast processing log gabor filter is used. It is used

in various applications as medical image processing, object

detection etc. The main aim behind this is to process the

image and use it in various applications using FPGA

platform. Field Programable Gate Array(FPGA) has an

huge embedded multipliers as well as large amount of

internal memory for real time application which is use in

digital image processing, by this way parallisiom is possible.

Hence, Field Programmable Gate Array always provides the

platform for real time image processing with higher

performance as compare to microprocessor and DSPs

(Digital Signal Processors). The FPGA image preprocessing

system architecture which uses Sobel algorithm and log

gabor filter to realize the edge detection is proposed here.

LabView NI Vision assistant is used for better performance

and for simplified design, by using NI Vision Assistant

different image pre-processing can be done.

Index Terms- Edge detection, Sobel operator, Log-Gabor filter,

LabVIEW 14.0, NI Vision Assistant, LabVIEW FPGA.

I-INTRODUCTION

Image processing is always having the important, broad,

fundamental and active area in the field of medical,

surveillance, authentication and many more application. In term

of medical disease, accurate results is always preferred, Medical

applications always consist with the different types of image

processing techniques like image enhancement method, image

pre-processing image post-processing, focused area selection

and object detection etc, and this all techniques/methods depend

on the edge detection, hence edge detection is always sensitive

and research area. Detection of some disease like tonsillitis,

tumor and fracture is depend on detection of edges of disease

and for this, pixel to pixel calculation is performed in image

processing. In this paper one of the finest edge detection method

is used that is sobel edge operator, mask of sobel operator is

work on the entire image and give us sharp and accurate edges

so that disease can be detect, and the algorithm is implemented

on FPGA kit. The main aim behind this procedure is to process

the image processing and use it in various applications for

medical application using FPGA. LabVIEW software is very

active and powerful tool, When it comes to creating DAQ

applications. LabVIEW includes a set of Virtual instruments

( VI ), that it let you configure, data acquire from, and transfer

data to data acquisition (DAQ) devices. Often, in LabVIEW one

device could perform a variety of functions, such as analog to

digital (A/D) conversion, digital to analog (D/A) conversion,

digital input and output, as well as counter/timer operation, Each

device supports different DAQ and signal generation speedswith

respect to image processing. Also, each data acquisition device

is designed for specific hardware, platforms and operating

systems for digital image processing. After reading the pixels of

an image, the algorithm is applied in VHDL, then processing the

image on FPGA as an hardware implementation, edge detected

image is displayed on LabVIEW front panel. The entire

simulation of the above process is done VHDL using XILINX

NI Sbrio 9631 FPGA, and to display input and output image

Lab VIEW is used. Field Programmable Gate Array (FPGA) is

a reconfigurable device and because of use of such devices the

time to market cost and time reduces. Also it becomes very easy

Paper Title:- LABVIEW DESIGN FOR EDGE DETECTION USING LOG GABOR FILTER FOR DISEASE DETECTION

ISSN:-2349-3585 |www.ijrdt.org 57

for the result verification and debugging processing. FPGA

implementation could become easy because of NI Vision

Assistant as it having scripts format which can easily

implemented on any image. Design scripts can covert for

LabVIEW code which is possible for edge detection. In

Labview image processing image acquisition, image processing,

different types of filter can use for noise remove per pose. With

the help of Math tool scripts kit we can call any mat lab function

to LabVIEW as this is the advantage for LabVIEW user. Here

Log Gabor filter is called from matlab for noise remove purpose

and for fast processing.

II.PROPOSED METHODS

A. Block Diagram for Disease Detection algoritham

Block diagram of disease detection module is shown below, it

having different blocksets which used for image processing

perpose. In LabVIEW for edge detection colo plane

extraction, image thresholding, IMAQ mathtool kit is

Fig 1. Proposed disease detection model

B. Image Acquisition with IMAQ and Preprocessing

In given design camera is used for real time application,

camera will capture image that will be normal image or

disease detected image and later it transfer to LabVIEW for

image processing. IMAQ tool detect input image, acquire it

for LabVIEW processing. In image processing first RGB

image converted in grayscale image with the help of color

plane extraction. Color plane extraction extract one basic color

from RGB image and at output grayscale image we found,

Here mathlookup (exponential) and image thresholding

function used for background color adjustment.

Fig 2. Image Acquition in LabVIEW

After image acquisition part LabVIEW apply some basic

processing for fine result and for better noise reduction so that

resultant output will be accurate.

C. Image processing by Log Gabor filtering

Basically Log Gabor filter is used for image filtering and for

best ridges of an image, which is shown in system.

Fig 3. Implementation of log gabor filter

D. Sobel Edge Operator

Sobel edge operator is nothing but a edge detecting

methodology used for finding edge detection in digital image

processing. Result of sobel edge detector is quite better as

compare to other edge detector like canny edge detector, Robert

operator, Prewit operator and laplasian filter. Mask of sobel

edge detector having two filter Hx filter and Hy filter, one for

horizanal pixel operation and other one is for vertical pixel

Paper Title:- LABVIEW DESIGN FOR EDGE DETECTION USING LOG GABOR FILTER FOR DISEASE DETECTION

ISSN:-2349-3585 |www.ijrdt.org 58

operation which mean horizontal edge detection and vertical

edge detection.

following is the sample matrix for vertical and horizontal edge

detection of sobel operator.

Here the direction of edges can be determine by using

following formula,

GM(x,y)= 22 HyHx

Fig 4. Sobel edge detection by LabVIEW VI

Fig 5. Result of sobel edge detector

III. LABVIEW CODING FOR DISEASE DETECTION

Here LabVIEW coding for tonsillitis disease detection is shown

below, which consist of an image acquisition, image

preprocessing, Log gabor filtering, mathlookup and image

thresholding.

Block diagram of disease detection module represent different

type of processes used for finding the disease detection. Block

diagram process all parameter and then results show on front

panel.

Fig 6- Block diagram of Disease detection module

Paper Title:- LABVIEW DESIGN FOR EDGE DETECTION USING LOG GABOR FILTER FOR DISEASE DETECTION

ISSN:-2349-3585 |www.ijrdt.org 59

IV. HARDWARE IMPLEMENTATION

In Digital image processing where the hardware and Software

both combination comes, the testing get reduced and

performance will increase, as software and hardware both

create the strongest parameter in medical application. As only

software has become less meaningful as image size and bit

depths grows larger. FPGA are used for high speed

processing in images. With the development of FPGA, a

large amount of data are captured using satellite and ground

based detection systems. Here in image processing, Labview

platform consist of NI Single Board RIO 9631 ( SbRIO 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 7. NI Sbrio FPGA kit

Implementation of disease detection module possible only when

the block diagram design will only in LabVIEW fpga tool. For

the implementation on LabVIEW FPGA, we required VI file

and Host file. NI SbRIO is an high speed FPGA tool used in

digital image processing.

Fig 8. FPGA Target VI.

V. 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.

Fig.9(a), Project Explorer

VI. VHDL Bit file Genaration

Below figure showing VHDL bit file genaration for hardware

implementation,

.Fig. 9 (b) VHDL Bit file Genaration

Fig 9 (c). Bit File generation report

Paper Title:- LABVIEW DESIGN FOR EDGE DETECTION USING LOG GABOR FILTER FOR DISEASE DETECTION

ISSN:-2349-3585 |www.ijrdt.org 60

After the code generation successfully, VHDL bit file dump into

SbRIO 9631 for the hardware implementation.When result

compare, found that processing time of software and hardware

is different, as hardware took less time for operation as compare

to software.

Fig 9 (d ). Code deployment process

VII. RESULTS

Result of disease detection by using Sobel operator, Log gabor

filter and with LabVIEW are shown below in fig 10(a), (b),(c),

and (d),

Fig 10(a) Disease detection with sobel operator

Fig 10(b) Disease detection with sobel operator

Fig 10(c) Disease detection with sobel operator

Fig 10(c) Disease detection with sobel operator

VIII. CONCLUSION

Here the paper proposed the disease detection module with the

help of sobel edge detection algorithm and log gabor filter. It

conclude that the LabVIEW is totally compatible for digital

image processing. Also paper proposed that the hardware and

software architecture for the sobelcedge detection which is

designed for the NI Single board RIO FPGA platform. As

LabVIEW is graphical programming language it is easy to

understand and also easy for implementation.

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ISSN:-2349-3585 |www.ijrdt.org 61

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