MATLAB: Error ‘Undefined variable “hisFtrs” or class “hisFtrs”.’

histogramMATLAB

histFtrs = cell(6,1);
start = 1;
for i = 1 : 6
    
    histFtrs{i} = hist(idx(start:start+size(features{i},2)),nWords)';
      %normalize
      histFtrs{i} = histFtrs{i}./sum(hisFtrs{i});
end
I am getting error as 
Undefined variable "hisFtrs" or class "hisFtrs".
Error in checker (line 30)
      histFtrs{i} = histFtrs{i}./sum(hisFtrs{i});
If anyone can help

Best Answer

At least in those lines of code you haven't defined hisFtrs variable. Can it be histFtrs?? If this is not the answer please provide the full code

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MATLAB: Matching an image with a database

BoF seems like a reasonable approach to this problem. Usually, you are working with a much larger set of images than just 5. Crucial to BoF are the feature points and descriptors you use to represent the images as well as the size of the visual vocabulary.

In the example below, I have used SURF features to detect feature points and extract sparse descriptors. I used SURF because they are scale and rotation-invariant. The Computer Vision System Toolbox has functions that enable you to do this:

http://www.mathworks.com/help/vision/feature-detection-extraction-and-matching.html

I then used the K-means algorithm to construct a visual vocabulary using 20 words. This function is part of the Statistics Toolbox. After creating a visual vocabulary, I created a bag-of-features representation for each image using this visual vocabulary. We now have a feature vector of length 20 for each of the 5 images. Applying K-means (again) on this to partition it into 2 sets gives the desired result. The fist four images are partitioned into 1 set and the last image to a different set.

%%Read images
im{1} = rgb2gray(imread('http://i.imgur.com/TMyflBl.png'));
im{2} = rgb2gray(imread('http://i.imgur.com/ozygW2g.png'));
im{3} = rgb2gray(imread('http://i.imgur.com/dGj8FNE.png'));
im{4} = rgb2gray(imread('http://i.imgur.com/VbTLPjG.png'));
im{5} = rgb2gray(imread('http://i.imgur.com/huj2El9.png'));
%%Detect and extract MSER features
detectFeatures = @(in) {detectSURFFeatures(in)}; 
regions = cellfun(detectFeatures,im);
extractAndTransposeFeatures = @(in,pts) extractFeatures(in,pts)';
features = cellfun(extractAndTransposeFeatures,im,regions,'UniformOutput',false);
figure;
for i = 1 : 5
    subplot(2,3,i);
    imshow(im{i});
    hold on;
    plot(regions{i});
end
%%Create a visual vocabulary with 20 words
nWords = 20;
%use kmeans for constructing the vocabulary.
[idx,centers] = kmeans([features{:}]',nWords);
%%BoF Feature Representation
histFtrs = cell(5,1);
for i = 1 : 5
    start = 1;
    histFtrs{i} = hist(idx(start:start+size(features{i},2)),nWords)';
      %normalize
      histFtrs{i} = histFtrs{i}./sum(hisFtrs{i});
  end
%display histograms
figure;
for i = 1 : 5;
    subplot(2,3,i);
    bar(histFtrs{i});
end
%%Partition images into 2 sets using kmeans
idx = kmeans([histFtrs{:}]',2)
% idx =
% 
%      2



%      2
%      2
%      2
%      1

Hope this helps. Bear in mind that you may need to do a lot more fiddling with some of the parameters and general approach for a more complicated problem.

MATLAB: How to solve Function ‘subsindex’ is not defined of class ‘strel’

You have overwritten the function imdilate with a variable imdilate. So now, the second time your code gets to that line it tries to subindex the variable imdilate with the iedge and se variables. The easy fix is by using a different name for the variable.

      im_dilate = imdilate(iedge, se); % dilation operation
	im_fill = im_fill(im_dilate, 'holes');
	our_images = im_fill & bw2;

Best Answer

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MATLAB: Matching an image with a database

MATLAB: How to solve Function ‘subsindex’ is not defined of class ‘strel’

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