Golden Retriever Image Retrieval Engine (GRIRE)

[brera]

Υλοποιημένο από φοιτητή της σχολής μας στα πλαίσια διπλωματικής εργασίας.

The GRire library is an open source, light-weight framework for implementing CBIR (Content Based Image Retrieval) methods. It contains various image feature extractors, descriptors, classifiers, databases and other necessary tools. Currently, the main objective of the project is the implementation of the BOVW (Bag of Visual Words) approach so, apart from the image analysis tools, to offer methods from the field of IR (Information Retrieval), e.g. weighting models such as SMART and Okapi, adjusted to meet the Image Retrieval perspective.

The purpose of the project is to help developers to create and distribute their methods and test the performance of their BOVW systems in actual databases with minimum effort and without having to deal with every aspect of the model. For example, a user who has created his own feature extractor and descriptor can integrate it into the GRire library, create a complete BOVW database and test it using GRire’s weighting and similarity models without having to implement anything else from scratch. So apart from a powerful and fast indexing and retrieving mechanism, GRire uses an extremely easy to use plugin system.

Read more about GRire: http://www.grire.net/

The source code and the compiled jar files of the core and the plugins are available at the Google Code page of GRire.

A list of the available plugin packs along with instructions is here.

For a quick tutorial about using GRire you can see the installation instructions and this example