Project No 3 [Shakeela Naz] [MSCS 17]

8/7/2019 Project No 3 [Shakeela Naz] [MSCS 17]

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DIGITAL IMAGE PROCESSING

PROJECT: 3

BY

NC Shakeela Naz

MSCS-17

DATED

5TH JAN, 2011



1. Problem definition :-

A program that reads a binary image in .PPM format after prompting the user for the file name of thatimage (There should be no other input.). The program will identify regions in the input image that are

potentially a human face.

2. Summary of algorithm :-Top-Down development approach is used for the required program.

Block diagram below shows the working of the program:-

See Appendix B for MATLAB implementation.

Reuse of outside code: None.



3. Example image and results of running the program on it :-

Above: Input Image TestImage1.ppm



Above: After Color Segmentation



Above: After converting to binary and applying morphological operations (opening by disk of size 1,

then filing holes and then opening again by disk of size 3)



Above: After labeling



Above: After discarding areas smaller than 200 pixels



Above: After discarding arms (by discarding areas with Eccentricity greater than 0.96)



Above: Color Segmented image after Morphological Processing and Connected region analysis



Above: Snapshot of output file OutPutTestImage1.ppm



Above: zoomed in snap-shot of OutPut file OutPutTestImage1.ppm



RESULTS:-

• Adjacent (overlapping) faces merged by program because of being part of same connected

region.

• Program successfully eliminated arm and elongated hand; but not curled hands (like fist). This

happened because arm and stretched / elongated hand and fingers had high Eccentricity, whilethe Eccentricity of fist/curled hands was closer to the Eccentricity of faces.



APPENDIX AREFRENCES:-

• MATLAB Central website : http://www.mathworks.com

• MATLAB Help.

http://www.mathworks.com/

http://www.mathworks.com/



APPENDIX BMATLAB CODE:-

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%--------------------------------------------%%%%%%%%%

%%%%%~*~*~*~ NC Shakeela Naz --- MSCS-17 ~*~*~*~%%%%%%%%%%~*~*~*~ Digital Image Processing ~*~*~*~%%%%%

%%%%%~*~*~*~ Project 3 ~*~*~*~%%%%%%%%%%~*~*~*~ 5th January, 2011 ~*~*~*~%%%%%

%%%%%%%%%--------------------------------------------%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%% Reading/Loading the PPM File %%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Load the Color Image(selected by user) in 'inImg' Variable(matrix).%

clc; % clear command window

clear; % clear work space

Imgread=0;while(Imgread==0)

[F,P]=uigetfile('*ppm;','Choose Image');

if F==0

return;else

PF=[ P , F ];

ext=PF(findstr(PF,'.')+1:end);

tryinRGB=imread(PF,'ppm');

Imgread=1;

catch lasterr

s1=lasterr;

if(s1=='Attempt to reference field of non-structure array.')

%if format mismatch; lasterr=Attempt to reference field of non-structure array.

Imgread=0

h=errordlg('File format mis-match','ERROR!')

uiwait(h);

uiresume;end

endend

end

figure,imshow(inRGB);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%

%%%%%%%%%%%%%%%%%%%%% Convert to HSV %%%%%%%%%%%%%%%%%



%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%

%

InImg=inRGB;

hsvImg=rgb2hsv(inRGB);[EndR EndC Channel]=size(hsvImg);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%

%%%%%%%%%%% FACE EXTRACTION %%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%

%

%

for i=1:EndR

for j= 1:EndC %%% only H and channel is needed

if ~(((0.01<=hsvImg(i,j,1) && hsvImg(i,j,1)<=0.06) || (0.96<=hsvImg(i,j,1) && hsvImg(i,j,1)<=1.0)))inRGB(i,j,1)=0;

inRGB(i,j,2)=0;

inRGB(i,j,3)=0;

endend

end


%convert color segmented img 2 grayscale......light greyshades correspond 2

%faces....others are to b discarded

graySeg=rgb2gray(inRGB);figure,imshow(graySeg);

BinSeg=graySeg;

BinSeg(BinSeg<80)=0;

BinSeg(BinSeg>=80)=1;

%binary morphology on BinSeg

%%

BinSeg=logical(BinSeg);figure,imshow(BinSeg);

se=strel('disk',1);

BinSeg=imopen(BinSeg,se);

figure,imshow(BinSeg);

BinSeg=imfill(BinSeg,'holes');




se=strel('disk',3);

BinSeg=imopen(BinSeg,se);


%%% Connected Region Analysis

BinSeg=bwlabel(BinSeg);

figure,imagesc(BinSeg);

%discard regions with areas less than 201

STATS = regionprops(BinSeg,'Area');

[c r]=size(STATS);

for i=1:c

if STATS(i).Area<=200 % if area of label c is less than or equal to 200

BinSeg(BinSeg==i)=0;end

end

BinSeg2=bwlabel(BinSeg);figure,imagesc(BinSeg2);

%discard regions with high Eccentricity

STATS2 = regionprops(BinSeg2,'Eccentricity');

[c2 r2]=size(STATS2);

for i=1:c2

if STATS2(i).Eccentricity>0.96 % if Eccentricity of label c is greater than 0.96BinSeg2(BinSeg2==i)=0;

end

end

[BinSeg3 n]=bwlabel(BinSeg2);

figure,imagesc(BinSeg3);

%Color Segmented image after Morphological Processing and Connected region analysis

for i=1:EndR

for j= 1:EndCif BinSeg3(i,j)==0

inRGB(i,j,1)=0;inRGB(i,j,2)=0;

inRGB(i,j,3)=0;

end

end

end


%Bounding boxes



STATS3 = regionprops(BinSeg3,'BoundingBox');

for j=1:n

x1=uint8(STATS3(j).BoundingBox(1,1));y1=uint8(STATS3(j).BoundingBox(1,2));

x2=uint8(x1 + STATS3(j).BoundingBox(1,3));y2=uint8(y1 + STATS3(j).BoundingBox(1,4));

InImg(y1,x1:x2,1:3)=255;

InImg(y2,x1:x2,1:3)=255;

InImg(y1:y2,x1,1:3)=255;

InImg(y1:y2,x2,1:3)=255;

x1=0;

x2=0;

y1=0;

y2=0;

end

% writing output file in work directory, in Output+Filename. ppm format, with bounding boxes on potential

face regions

figure,imshow(InImg);

d='OutPut';

fileOut=[d,F];

imwrite(InImg,fileOut,'ppm');

Project No 3 [Shakeela Naz] [MSCS 17]

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