Use of Image Subset Features in Image Retrieval with Self-Organizing Maps

In content-based image retrieval (CBIR), the images in a database are indexed on the basis of low-level statistical features that can be automatically derived from the images. Due to the semantic gap, the performance of CBIR systems often remains quite modest especially on broad image domains. One method for improving the results is to incorporate automatic image classification methods to the CBIR system. The resulting subsets can be indexed separately with features suitable for those particular images or used to limit an image query only to certain promising image subsets. In this paper, a method for supporting different types of image subsets within a generic framework based on multiple parallel Self-Organizing Maps and binary clusterings is presented.

• Type: Conference
• Year: 2004
• Where: CIVR
• Authors: Markus Koskela, Jorma Laaksonen, Erkki Oja
• Keywords: Cbir System, CIVR 2004, Image, Image Subsets