MOTION ANALYSER USING IMAGE PROCESSING

SUBMITTED TO- SUBMITTED BY-MR. HEMANT MEENA TOSHIM KUMAR(2013UEE1593) ASSIT. PROFESSOR KHINYA RAM(2013UEE1597)ELECT. ENGG DEPT. BANKESH MEHTA(2013UEE1614)MNIT JAIPUR MANISH GUPTA(2013UEE1762)

CONTENT

• INTRODUCTION• OBJECT REPRESENTATION• WORKING• APPLICATION• MATLAB DEMONSTRATION

INTRODUCTION Here in this project our main focus is in

determining the positions, speed and other relevant information of moving objects in image sequence.

To track an object over a sequence of image. It is a method of following an object through

successive image frame to determine its relative movement with respect to other object.

OBJECT REPRESENTATION

In a tracking scenario, an object can be defined as anything that is of interest for future analysis. Object can be represented by their shapes. Object shape representations commonly employed for tracking are-

Points- the object is represented by a point, that is centroid or set of points. Point representation is suitable for tracking objects that occupy small region of an image.

Primitive geometric shape-object shape is represented by a rectangle, ellipse etc these are suitable for representing simple rigid objects and non rigid objects.

WORKING-

Analysis of two consecutive frames are taken into account, in which the histogram of key region parts of the frames is analyzed.

Histogram is then compared with the determined threshold value.

The key region should be at least 3-pixel-wide profile of the image along the road.

Then a median filtering operation is first applied to the profile (key region) of each frame and one-pixel-wide profile is extracted.

The Difference of two profiles is then compared to detect whether there is any displacement or motion.

When there is motion, the differences of the profiles are greater than the case when there is no motion.

Thus motion can be detected by selecting an appropriate threshold value. The size of the profile plays an essential role and hence is an important parameter.

Let us consider an object moving from left to right-

The object starting from left.

The object reached to the center

The object on extreme right

First we click the picture of moving object and it is stored in matlab in the form of matrix of appropriate resolution.

Then again we take the image of the moving object and that is also stored in matlab in the form of matrix.

Then further both the matrices are compared with appropriate matlab program .

And finally the result is obtained i.e. object is moving in which direction and what is its speed.

APPLICATION-

The first most important application is in radar to find velocity range and position of the object.Synthetic aperture radar (SAR) is a technique for taking extremely high- resolution radar images, typically of ground features from an airplane. In spotlight mode, the radar beam is focused on one patch of ground as the aircraft flies from point A to point B. Returned signals are collected continuously to create a high-resolution image integrated over a very large aperture.

Radar flying object tracking-

Another use is in speed limit enforcement by traffic police.Speed limit enforcement is the action taken by appropriately empowered authorities to check that road vehicles are complying with the speed limit in force on roads and highways. Methods used include roadside speed traps set up and operated by the police and automated roadside 'speed camera' systems which may incorporate the use of an automatic number plate recognition system. Traditionally, the police would have used stopwatches to measure the time taken for a vehicle to cover a known distance, but more recently, they have had speed guns and automated in-vehicle systems at their disposal.

MATLAB DEMONSTRATION-Clcclear all A=imread('1.png'); B=imread('2.png'); subplot(2,1,1) image(A); subplot(2,1,2) image(B); n=size(B,2); p=0; q=0; for i=1:1:n G=mshiftleft(B,i); p=p+1; G2=sum(sum(sum(G-A))); if G2==0 break end end For i=1:1:n G=mshiftright(B,i); q=q+1; G2=sum(sum(sum(G-A))); If G2==0 break endend

d=2; % perpendicular distance of camera from road is 2 m l=98*d*pi/180; % field of view of camera is 65*98 degree t=.5; %time between two image is 0.5 seconds if p>q fprintf('object is moving toward right\n'); s=q*98*d*pi/(300*180); fprintf('speed of object is %.2f m/s\n',s); end if p<q fprintf('object is moving toward left\n'); s=p*98*d*pi/(300*180); fprintf('speed of object is %f m/s\n',s); end

Representation of two images-