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http://dx.doi.org/10.9717/kmms.2016.19.7.1116

Efficient Image Segmentation Algorithm Based on Improved Saliency Map and Superpixel  

Nam, Jae-Hyun (Dept. of Cpmputer Eng., SunMoon University)
Kim, Byung-Gyu (Dept. of IT Eng., Sookmyung Women's University)
Publication Information
Journal of Korea Multimedia Society / v.19, no.7, 2016 , pp. 1116-1126 More about this Journal
Abstract
Image segmentation is widely used in the pre-processing stage of image analysis and, therefore, the accuracy of image segmentation is important for performance of an image-based analysis system. An efficient image segmentation method is proposed, including a filtering process for super-pixels, improved saliency map information, and a merge process. The proposed algorithm removes areas that are not equal or of small size based on comparison of the area of smoothed superpixels in order to maintain generation of a similar size super pixel area. In addition, application of a bilateral filter to an existing saliency map that represents human visual attention allows improvement of separation between objects and background. Finally, a segmented result is obtained based on the suggested merging process without any prior knowledge or information. Performance of the proposed algorithm is verified experimentally.
Keywords
Image Segmentation; Superpixel; Saliency Map; Merging Algorithm;
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