Abstract
Multimedia data, typically image data, is increasing rapidly across the Internet and elsewhere. To keep pace with the increasing volumes of image information, new techniques need to be investigated to retrieve images intelligently and efficiently. Content-based image retrieval is always a challenging task. In this paper, a stochastic model, called Markov Model Mediator (MMM) mechanism, is used to model the searching and retrieval process for content-based image retrieval. Different from the common methods, our stochastic model carries out the searching and similarity computing process dynamically, taking into consideration not only the image content features but also other characteristics of images such as their access frequencies and access patterns. Experimental results demonstrate that the MMM mechanism together with the stochastic process can assist in retrieving more accurate results for user queries.
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Shyu, ML., Chen, SC., Luo, L., Shu, CM. (2002). A Stochastic Model for Content-Based Image Retrieval. In: Chen, YC., Chang, LW., Hsu, CT. (eds) Advances in Multimedia Information Processing — PCM 2002. PCM 2002. Lecture Notes in Computer Science, vol 2532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36228-2_29
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DOI: https://doi.org/10.1007/3-540-36228-2_29
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