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I am doing a project on Writer Identification. I want to extract HOG features from Line Images of Arabic Handwriting. And than use Gaussian Mixture Model for Classification. The link to the database containing the line Images is : http://khatt.ideas2serve.net/

So my questions are as follows;

  1. There are three folders namely Test, Train and Validate. So, from which folder do I need to extract the features. And for what purpose should we use each of the folders.
  2. Do we need to extract the features from individual images and merge them or is there any method to extract features of all the images together.
JUHA HANSDA
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2 Answers2

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Test, Train and Validate

Read this stats SE question: What is the difference between test set and validation set?

This is basic machine learning, so you should probably go back and review your course literature, since it seems like you're missing some pretty important machine learning concepts.

Do we need to extract the features from individual images and merge them or is there any method to extract features of all the images together.

It seems, again, like you're missing basic concepts here. Histogram of oriented gradients subdivides the image and finds the oriented gradient. See this SO question for examples of hos this looks.

The traditional way of using HoG is: for each image in your training set, you extract the HoG, use these to train a SVM, validate the training with the validation set, then actually use the trained SVM on the test set.

Community
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beerbajay
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You need to extract the HOG features from each image separately. Furthermore, you have to resize all images to be of the same size, otherwise all your HOG vectors will be of different length.

You can use the extractHOGFeatures function in MATLAB. See this example.

Dima
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