Software for Image classification

Question

Currently I am working for a project to classify a given set of test images into one of the 5 predefined categories. I implemented Logistic Regression with a feature vector of 240 features for each image and trained it using 100 images/ category. The learning accuracy I achieved was ~98% for each category, whereas when tested on validation set consisting of 500 images (100 images/category), only ~57% images were rightly classified.

Please suggest me few libraries/tools which I can use (preferably based on Neural Network) in order to attain higher accuracy.

I tried using a Java based tool, Neurophy (neuroph.sourceforge.net) on windows but, it didn't run as expected.

Edit: The feature vector were already provided for the project. I am also looking for a better feature extraction tool for Images.

Answer 1

You can get help from this paper Image Classification

In My opinion, SVM is relatively better than logistic regression when it comes to multi-class response problems. We use it in e commerce classification of product where there are 1000s of response level and thousands of features.

Answer 2

Based on your tags I assume you would like a python package, scikit-learn has good classification routines: scikit-learn.org.

Answer 3

I have had good success using the WEKA tools, you need to isolate the feature set that you are interested in and then apply a classifier from this library. The examples are very clear. http://weka.wikispaces.com