Evaluating Search Engines in Image retrieval Based on Text and Content-Based Indexing

The main pupose of this study was to identify capabilities and differences among search engines in retrieving images from a text-based and content-based indexing approach. The present study was an applied research using an evaluative method.Five accessible search engines, e.g., Google, Yahoo, Picsearch, Lycos,and Exalead were selected as the research population. To gather the required information, observation and a checklist were developed based on three major components (criteria search engines for images, image retrieval based on content and context and content), with their eleven subparts. Findings showed that "Google" had the most desirable condition in retrieving images in comparison with other search engines and it was identified as the most efficient search engine. In next positions, "Yahoo", "Lycos",: Exalead", "Picsearch" were respectively ranked based on frequency distribution. Also regarding the research hypothesis, findings showed that there was a significant difference among independent groups in terms of image retrieval. The results indicated that general search engines had good performance in comparison to specialized ones. So the users of images on the Web can select the appropriate search engine based on their needs.