Question

My goal is to implements different image classification methods to show how they function and the advantages and disadvantages behind such methods. The ones I want to try and implement using Java include;

Minimum distance classifier

k-nearest neighbour classifier.

I was wondering what can be used to accomplish my task that already exists in Java so that I can alter the way the algorithms operates.

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Solution

Although not entirely sure this is what you are looking for (sorry, your question is a bit unclear), if what you want is a library / system to help you with the classification part of the work, then you may want to look at Weka (http://www.cs.waikato.ac.nz/ml/weka/), in my opinion the best Java library for data mining experimentation.

If, instead, you are looking for algorithms that would allow you to analyze images in order to extract features that can, in turn, be used to perform the classification, you may want to start with targeted descriptions of such algorithms in Java, such as those found in the nice on-line book Java Image Processing Cookbook by Rafael Santos; here's a direct link to the section "A Brief Tutorial on Supervised Image Classification".

OTHER TIPS

You can also use RapidMiner with IMMI (IMage MIning) extension:

http://www.burgsys.com/mumi-image-mining-community.php

For image classification you can use for example global feature extraction and then use some classification algorithm (e.g. Artificial Neural Networks).

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