Review on Content-Based Image Retrieval Reliance on User Intention
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 12
Abstract
The search engine returns thousands of images ranked by the keywords extracted from the surrounding text. It is well known that text-based image search suffers from the ambiguity of query keywords. The keywords provided by users tend to be short. They cannot describe the content of images accurately. The search results are noisy and consist of images with quite different semantic meanings. For example, if a user wants to search for an “apple” image, he/she may request a query search using the keyword “apple” to the corresponding image search engine. The meanings of the word “apple” include apple fruit, apple computer, and apple ipod. The search results will contain different categories, such as “green apple,” “apple,” “apple logo,” and “iphone” because of the ambiguity of the word “apple”. This leads to ambiguous & noisy search results which are not satisfactory to fulfil the user query request. In order to solve the ambiguity, additional information has to be used to capture users’ search intention.
Authors and Affiliations
Sumit Dhotre, Sathishkumar Penchala
Keywords
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