PicSOM - content-based image retrieval with self-organizing maps

We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing maps (TS-SOMs). Given a set of reference images, PicSOM is able to retrieve another set of images which are similar to the given ones. Each TS-SOM is formed with a dierent image feature representation like color, texture, or shape. A new technique introduced in PicSOM facilitates automatic combination of responses from multiple TS-SOMs and their hierarchical levels. This mechanism adapts to the user's preferences in selecting which images resemble each other. Thus, the mechanism implements a relevance feedback technique on content-based image retrieval. The image queries are performed through the World Wide Web and the queries are iteratively re

• Type: Journal
• Year: 2000
• Where: PRL
• Authors: Jorma Laaksonen, Markus Koskela, Sami Laakso, Erkki Oja
• Keywords: Content-based Image Retrieval, Image Feature Representation, Images, PRL 2000