Lire-project.net Website Review

LIRE is a Ja*a library that provides a simple way to retrieve images and photos based on color and texture characteristics. LIRE creates a Lucene index of image features for content based image retrieval (CBIR) using local and global state-of-the-art methods. Easy to use methods for searching the index and result browsing are provided. Best of all: it's all open source. LIRE is successfully used at the WIPO, a United Nations Agency, to search in millions of trademark images and the Danish National Police to find similar scenes and to detect near duplicates. LIRE also works well with the Apache Solr search server. LIRE works on platforms supporting Ja*a 8 and has been tested on Windows and Linux. Test it on a million images with the web demo LIRE comes without secrets. All the state of the art algorithms are available in source. Well known and well performing local and global features are integrated. Using approximate search LIRE scales well to millions of images. Take control over every step in the process, tinker with extraction, indexing and search. Fresh & new algorithms from the visual information retrieval community. No need to pay a high price when it comes for free. No need to look for proprietary solutions, when source code is available. LIRE is published under the viral OSS Licene, the GNU Public License. Therefore, it will stay free. written by Mathias Lux and Oge Marques is available on Amazon For many of the global descriptors LIRE is the de-facto reference implementation, also in research. Content based image retrieval & visual information retrieval experts at your service for affordable rates. I used LIRE in several projects. And I am really impressed. It is very flexible, provides powerful tools and at the same time it is easy to LIRE was a huge help for our research in multimedia by allowing us to quickly extract visual features for our baseline processing pipeline. We used Lire for the extraction of visual features for the YFCC100m dataset. It is a great tool providing a broad set of different image