Abstract
In this paper, we propose a novel feature descriptor named quantized local trio pattern (QLTP) for multimedia image retrieval application. The QLTP extracts quantized edge information from the pixels in a specified neighborhood. QLTP integrates the quantization and trio patterns for image retrieval. Performance of the QLTP is evaluated by conducting experiments on Corel-10,000 databases. Experimental results exhibit an improvement in terms of avg. retrieval precision (ARP) and avg. retrieval rate (ARR) as compared to the other related methods.
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Rohini, P., Shoba Bindu, C. (2019). Quantized Local Trio Patterns for Multimedia Image Retrieval System. In: Saini, H., Singh, R., Kumar, G., Rather, G., Santhi, K. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 65. Springer, Singapore. https://doi.org/10.1007/978-981-13-3765-9_12
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DOI: https://doi.org/10.1007/978-981-13-3765-9_12
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