Content Based Image Retrieval and Clustering: A Brief Survey
Huiyu Zhou, Abdul H. Sadka, Mohammad R. Swash, Jawid Azizi and Abubakar S. Umar
Affiliation: Electronic and Computer Engineering, School of Engineering and Design, Brunel University, West London, UB8 3PH, UK.
Keywords: Content-based image retrieval, feature, similarity, supervised clustering, unsupervised clustering
Image retrieval is an important research area, where a variety of clustering techniques have been introduced in the literature to categorise and group the image resources according to their characteristics. In this paper, we provide a brief survey of supervised and unsupervised clustering methods that have been patented up to date in accordance with their applications in image retrieval. In particular, we focus on introducing the concepts generated within these patents based on the limitations found in the classical image retrieval systems. Finally, a summary is made and future work in image retrieval is outlined.
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