Abstract
An important step in content-based image retrieval is finding an interesting object within an image. We propose a method for extracting an interesting object from a complex background. Interesting objects are generally located near the center of the image and contain regions with significant color distribution. The significant color is the more frequently co-occurred color near the center of the image than at the background of the image. A core object region is selected as a region a lot of pixels of which have the significant color, and then it is grown by iteratively merging its neighbor regions and ignoring background regions. The final merging result called a central object may include different color-characterized regions and/or two or more connected objects of interest. The central objects automatically extracted with our method matched well with significant objects chosen manually.
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Kim, S., Park, S., Kim, M. (2003). Central Object Extraction for Object-Based Image Retrieval. In: Bakker, E.M., Lew, M.S., Huang, T.S., Sebe, N., Zhou, X.S. (eds) Image and Video Retrieval. CIVR 2003. Lecture Notes in Computer Science, vol 2728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45113-7_5
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DOI: https://doi.org/10.1007/3-540-45113-7_5
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