Abstract
Information retrieval in the form of documents, images is playing a key role in day-to-day life of humans. Real world applications scenario is changing daily, so as the improvement is also becomes a necessary. Various approaches were proposed for retrieval, but all the input images were considered under proper illumination conditions. If the images suffered with illumination angle color and viewing angle changes then it’s very difficult to retrieve similar images. We propose a system which can deal with illumination angle and color variations. Experiments were conducted on ALOI (Amsterdam Library of Object Images) dataset, which is a collection of one thousand objects each with hundred similar images. These images were recorded under changing the illumination angle, color and viewing angle. Experimental results prove that the proposed approach outperforms well in terms of retrieval efficiency \(\dots \)
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Neelima, N., Koteswara rao, P., Sai Praneeth, N., Mamatha, G.N. (2017). An Integrated Framework to Image Retrieval Using L*a*b Color Space and Local Binary Pattern. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_25
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DOI: https://doi.org/10.1007/978-981-10-4859-3_25
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