# Matlab Task on Computer Programming & Numerical Methods

A=imread(‘one.png’)
signImage=rgb2gray(A);
figure(1)
imshow(signImage)
%Detect features of first image that is read above%
signPoints=detectSURFFeatures(signImage)
figure(3)
imshow(signImage)
title(‘100 strongest features from sign image’)
hold on
%Top 100 strongest features
plot(selectStrongest(signPoints,100))

[signFeatures2, signPoints2] = extractFeatures(signImage, signPoints)

B=imread(‘two.png’)
signImage2=rgb2gray(B);
figure(4)
imshow(signImage2)
%Detect features of first image that is read above%
signPoints2=detectSURFFeatures(signImage2)
figure(5)
imshow(signImage2)
title(‘100 strongest features from sign image’)
hold on
%Top 100 strongest features
plot(selectStrongest(signPoints2,300))
[signFeatures2, signPoints2] = extractFeatures(signImage2, signPoints2)

%Punitive point matches in both the images%

picPairs=matchFeatures(signFeatures, signFeatures2);
matchedSignPoints = signPoints(picPairs(:,1),:);
matchedFindPoints = signPoints2(picPairs(:,2),:);
figure(6)
showMatchedFeatures(signImage,signImage2,matchedSignPoints, matchedFindPoints, ‘montage’)
title(‘Matched points both images’)

%Locate objects using Punitive matches%
%[tform, inlierBoxPoints, inlierScenePoints] =estimateGeometricTransform(matchedSignPoints, matchedFindPoints);
%figure;
%showMatchedFeatures(signImage, signImage2, inlierBoxPoints,inlierScenePoints, ‘montage’);
%title(‘Matched Points (Inliers Only)’);

# Python Task on Objects and Algorithms

files=[“in_abc10.txt”,”in_abc100.txt”]
outFiles=[“out_abc10a.txt”,”out_abc100a.txt”]
finalOutputFile=[“out10b.txt”,”out100b.txt”] Continue reading