Object Detection & Description

8/3/2019 Object Detection & Description

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UNIVERSITY TEKNIKAL MALAYSIA MELAKA

Object Detection & De-

scription

Engr. Khairul Muzzammil b. Saipullah


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Content

Thresholding Object detection (Basic) Face detection

Object description (Feature Extraction)


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Thresholding

Convert image into binary image (Black or White) Ex: if pixel >150 -->255, pixel 150)=255;B(A


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Thresholding

Auto thresholding using Otsu thresholding Optimum division between foreground and background

A=imread('images.jpg');A=rgb2gray(A);B=im2bw(A);imshow(B);


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Thresholding

Auto thresholding using Otsu thresholding Optimum division between foreground and background

>> a=imread('coin.jpg');>> b=im2bw(rgb2gray(a));>> imshow(~b)%inverse black and white


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Object Detection

Using Otsu thresholding try to locate the ball

>> A=imread('ball.jpg');>> b=im2bw(rgb2gray(A));>> imshow(b)


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Object Detection

Remove the noise using morphology method in order tomake the image clearer

>> A=imread('ball.jpg');>> b=im2bw(rgb2gray(A));>>P=3000;>> BW2 = bwareaopen(b,P);>>BW3 = bwmorph(BW2,'dilate');

>>imshow(BW3)


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Object Detection

Get the top, bottom, left and right boundary of the object Get the center coordinate

X=left+(Right-left)/2 Y=top+(down-top)/2

A=imread('ball.jpg');b=im2bw(rgb2gray(A));P=3000;BW2 = bwareaopen(b,P);BW3 = bwmorph(BW2,'dilate');

[cx,cy,hh,ww]=findboundary(BW3);imshow(BW3);hold on;plot(cx,cy,'r*');plot(cx,cy-hh/2,'r*');plot(cx,cy+hh/2,'r*');plot(cx+ww/2,cy,'r*');plot(cx-ww/2,cy,'r*');


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Object Detection

Finally, you can get the region of the object on the original image

A=imread('ball.jpg');b=im2bw(rgb2gray(A));P=3000;BW2 = bwareaopen(b,P);BW3 = bwmorph(BW2,'dilate');[cx,cy,hh,ww]=findboundary(BW3);imshow(A);rectangle( 'Position',[cx-hh/2,cy-ww/2,hh,ww],'EdgeColor','r', 'LineWidth',2);


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FACE DETECTION


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Copy face_detection_aruma.zip , unzip it and drag it toMatlab Current Folder

First Method


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Double click the folder , subfolders and the files will ap-pear as shown.


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Double click at facedetection.m and at the top of the file,edit the input image part.ex:i=imread(face_database/face4.jpg);

Click run and usually for the first time this window will bepopped up

Click Change Directory


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For the face4.jpg image, the outputs will be shown asbelow

First Method Outputs


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Copy FDMver1.0.zip , unzip it and drag it to Matlab Cur-rent Folder

Second Method


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Under that folder, Double click at ex01.m and run it.


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The output will appear as shown. Try to change the inputto another picture and see the result.

Second Method Output


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Description using KEY-

POINT


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Keypoint

The important of significant point in and object Used to describe the object Example

Laplacian of Gaussian (LOG) Harries Corner Susan Corner Gilles Harris Laplace


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keypoint

Open keypointExtraction folder. Open test.m and run it Change the filename in the test.m with other image file

and test.

Documents

Object Detection & Description