Abstract
The keyword-based images search engine like Google or Yahoo may return a large number of junk images which are irrelevant to the given keyword-based queries. In this paper, an interactive approach is developed to filter out the junk images from the keyword-based Yahoo image search results through Yahoo’ Boss API. The framework of multi-threaded processing is proposed to incorporate an image analysis algorithm into the text-based image search engines. It enhances the capability of an application when downloading images, indexing, and comparing the similarity of retrieved images from diverse sources. We also propose an efficient color descriptor technique for image feature extraction, namely, Auto Color Correlogram and Correlation (ACCC) to improve the efficiency of image retrieval system and reduce the processing time. The experimental evaluations based on the coverage ratio measure show that our scheme significantly improves the retrieval performance over the existing image search engines.
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Premchaisawadi, W., Tungkatsathan, A. (2011). On-Line Image Search Application Using Fast and Robust Color Indexing and Multi-Thread Processing. In: Ao, SI., Gelman, L. (eds) Electrical Engineering and Applied Computing. Lecture Notes in Electrical Engineering, vol 90. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1192-1_22
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DOI: https://doi.org/10.1007/978-94-007-1192-1_22
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