LIRE is a Java library that provides a simple way to retrieve images and photos based on color and texture characteristics (Lux, 2015 AU130: The citation "Lux, 2015" matches multiple references. Please add letters (e.g. "Smith 2000a"), or additional authors to the citation, to uniquely match references and citations. ). LIRE creates a Lucene index of image features for content based image retrieval (CBIR) using local and global state-of-the-art methods (Lux, 2015 AU131: The citation "Lux, 2015" matches multiple references. Please add letters (e.g. "Smith 2000a"), or additional authors to the citation, to uniquely match references and citations. ). 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 (Lux, 2015 AU132: The citation "Lux, 2015" matches multiple references. Please add letters (e.g. "Smith 2000a"), or additional authors to the citation, to uniquely match references and citations. ).
Published in Chapter:
The Image as Big Data Toolkit: An Application Case Study in Image Analysis, Feature Recognition, and Data Visualization
Kerry E. Koitzsch (Kildane Software Technologies Inc., USA)
Copyright: © 2018
|Pages: 52
DOI: 10.4018/978-1-5225-3142-5.ch018
Abstract
This chapter is a brief introduction to the Image As Big Data Toolkit (IABDT), a Java-based open source framework for performing a variety of distributed image processing and analysis tasks. IABDT has been developed over the last two years in response to the rapid evolution of Big Data architectures and technologies, distributed and image processing systems. This chapter presents an architecture for image analytics that uses Big Data storage and compression methods. A sample implementation of our image analytic architecture called the Image as Big Data Toolkit (IABDT) addresses some of the most frequent challenges experienced by the image analytics developer. Baseline applications developed with IABDT, status of the toolkit and directions for future extension with emphasis on image display, presentation, and reporting case studies are discussed to motivate our design and technology stack choices. Sample applications built using IABDT, as well as future development plans for IABDT are discussed.