Content-based image retrieval has shown to be more and more useful for several application domains, from audiovisual media to security. As content-based retrieval became mature, different scientific applications were revealed client for such methods. More recently, botanical applications generated very large image collections and then became very demanding content-based visual similarity computation. In this paper, we describe low-level feature extraction for visual appearance comparison between genetically modified plants for gene expression studies.
Content-based image retrieval in botanical collections for gene expression studies
IEEE International Conference on Image Processing 2005 ; 3 ; III-1240
2005-01-01
495195 byte
Conference paper
Electronic Resource
English
Content-based image retrieval in botanical collections for gene expression studies
British Library Conference Proceedings | 2005
|Here's Waldo: Content Based Image Retrieval
British Library Online Contents | 1998
|A content-based image retrieval system
British Library Online Contents | 1998
|Learning semantics in content based image retrieval
IEEE | 2003
|Texture Classification for Content-Based Image Retrieval
British Library Conference Proceedings | 2001
|