An explosion of digital photography technologies that permit quick and easy uploading of any image to the web, coupled with the proliferation of personal, recreational users of the internet over the past several years have resulted in millions of images being uploaded on the World Wide Web every day. Most of the uploaded images are not readily accessible as they are not organized so as to allow efficient searching, retrieval, and ultimately browsing. Currently major commercial search engines utilize a process known as Annotation Based Image Retrieval to execute search requests focused on retrieving an image. Despite the fact that the information sought is an image, the ABIR technique primarily relies on textual information associated with an image to complete the search and retrieval process. Using the game of cricket as the domain, this article compares the performance of three commonly used search engines for image retrieval: Google, Yahoo and MSN Live. Factors used for the evaluation of these search engines include query types, number of images retrieved, and the type of search engine. Results of the empirical evaluation show that while the Google search engine performed better than Yahoo and MSN Live in situations where there is no refiner, the performance of all three search engines dropped drastically when a refiner was added. Further research is needed to overcome the problems of manual annotation embodied in the annotationbased image retrieval problem.
Fendley, Ryan and Kidambi, Phani, "Benchmarking Web-Based Image Retrieval" (2010). AMCIS 2010 Proceedings. 105.