How to classify images depending on the shape of each image's object ?

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Mohamed Elbeialy
Mohamed Elbeialy 2021 年 4 月 21 日
コメント済み: Amit 2021 年 6 月 5 日
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Mohamed Elbeialy
Mohamed Elbeialy 2021 年 4 月 24 日
5 classes of cars, flowers, buidlings, trees, dogs. The point is to classify them according to the shape of the object inside each image. Using max value of the image is just a hint. if you have another way to determine the shape of object, ues it .
Amit
Amit 2021 年 6 月 5 日
Follow following steps,
  1. First of all you need to binarize the image and find edges of image using canny edge detection.
  2. Then you need use regionprops to extract various isolated regions in the image.
  3. You need to find centroid of regions.
  4. Then at various angles, you can find distance between centroid of region and point on edge of image.
  5. This makes your shape descriptors.
  6. You can compare these descriptors with descriptors of known share to categorize your query or unkown object.
This should work for you.
I have my IEEE paper published regarding above process, you can send request to me on, amit.kenjale@gmail.com, I will send you my IEEE paper where this process is explained in details with images showing intermediate results.

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回答 (3 件)

Mahesh Taparia
Mahesh Taparia 2021 年 4 月 24 日
Hi
There is already an existing answer similar to this problem. You can refer this link for that.
  1 件のコメント
Mohamed Elbeialy
Mohamed Elbeialy 2021 年 4 月 24 日
This link does not have any relation with my question.

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Image Analyst
Image Analyst 2021 年 4 月 24 日
Try the transfer learning example with CNN/AlexNet. There should be demos in the Deep Learning Toolbox.
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Mohamed Elbeialy
Mohamed Elbeialy 2021 年 4 月 27 日
Here it is. how to make sure that the network will detect all random shapes of all images inside the imageData store
Image Analyst
Image Analyst 2021 年 4 月 27 日
To get a binary image mask of inside where you traced the outline:
binaryImage = grayImage < someValue;
You'd have to train (label) your training images all with the outline and with the class you know them to be (car, dog, etc.)

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Walter Roberson
Walter Roberson 2021 年 4 月 25 日
imageInputLayer([227 227 3],"Name","data","Normalization","rescale-zero-one")
This will rescale each input image to have a maximum value of 1.
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Mohamed Elbeialy
Mohamed Elbeialy 2021 年 4 月 27 日
here it is, however, I stucked with (gTruth ) which does not allow me to insert all imageData store images [imds,blds] = objectDetectorTrainingData(gTruth)
Image Analyst
Image Analyst 2021 年 4 月 27 日
You asked: "I do find the code for detecting object inside image, but I do not know how to apply to the whole imageDatastore." So, try this:
ds = imageDatastore('*.png')
numFiles = numel(ds.Files)
% Apply "code for detecting object inside image" to "the whole
% imageDatastore" - apply to every image in the image datastore.
for k = 1 : numFiles
thisFullFileName = ds.Files{k};
fprintf('Analyzing #%d of %d : "%s" ...\n', k, numFiles, thisFullFileName);
theImage = imread(thisFullFileName);
imshow(theImage);
[folder, baseFileNameNoExt, ext] = fileparts(thisFullFileName);
title(baseFileNameNoExt, 'Interpreter', 'none');
drawnow;
% Now give code to do something to analyze theImage...
% Put your existing code "for detecting object inside image" here:
end

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