A World Wide Web Region-Based Image Search Engine

In this paper the development of an intelligent image content-based search engine for the World Wide Web is presented. Information Web Crawlers continuously traverse the Internet and collect images that are subsequently indexed based on integrated feature vectors. As a basis for the indexing, a novel K-Means segmentation algorithm is used, modified so as to take into account the coherence of individual regions. Based on the extracted regions, characteristic features are estimated using color, texture and shape/region boundary information. These features along with additional information are stored in a database. The user can access and search this indexed content through the Web with an advanced interface. Experimental results demonstrate the performance of the system, which can be reached in a publicly accessible web site.

• Type: Conference
• Year: 2001
• Where: ICIAP
• Authors: Ioannis Kompatsiaris, Evangelia Triantafyllou, Michael G. Strintzis
• Keywords: Content-Based Search Engine, ICIAP 2001, Image Processing, Information Web Crawlers, K-Means Segmentation Algorithm