Title :
Saliency-seeded localizing region-based active contour for automatic natural object segmentation
Author :
Shangbing Gao ; Jian Yang
Author_Institution :
Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
In this paper, we propose a new saliency-seeded active contour based automatic natural object segmentation method. It is known that using saliency regions or pixels can easily get the approximately location of the desired object in the map. The salient object points are employed as the seeds of convex hull to generate the initial contour for our automatic object segmentation system. In contrast with localizing region-based active contours that require considerable user interaction, the proposed method does not require it, i.e., the segmentation task is fulfilled in a fully automatic manner. Extensive experiments results on a large variety of natural images confirm that our framework can reliably and automatically extract the object from the complex background.
Keywords :
feature extraction; image segmentation; automatic natural object segmentation system; complex background object extraction; convex hull; image pixels; saliency regions; saliency-seeded localizing region-based active contour generation; salient object points; Active contours; Algorithm design and analysis; Image segmentation; Noise; Object segmentation; Pattern recognition; Visualization;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4