SnakeCut: an Integrated Approach Based on Active Contour and GrabCut for Automatic Foreground Object Segmentation
- Autores: Surya Prakash, R. Abhilash, Sukhendu Das
- Localización: ELCVIA. Electronic letters on computer vision and image analysis, ISSN-e 1577-5097, Vol. 6, Nº. Extra 3, 2007 (Ejemplar dedicado a: Special Issue on Vision and Multimedia Processing), págs. 13-29
- Idioma: inglés
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Resumen
Interactive techniques for extracting the foreground object from an image have been the interest of research in computer vision for a long time. This paper addresses the problem of an efficient, semi-interactive extraction of a foreground object from an image. Snake (also known as Active contour) and GrabCut are two popular techniques, extensively used for this task. Active contour is a deformable contour, which segments the object using boundary discontinuities by minimizing the energy function associated with the contour. GrabCut provides a convenient way to encode color features as segmentation cues to obtain foreground segmentation from local pixel similarities using modified iterated graph-cuts. This paper first presents a comparative study of these two segmentation techniques, and illustrates conditions under which either or both of them fail. We then propose a novel formulation for integrating these two complimentary techniques to obtain an automatic foreground object segmentation. We call our proposed integrated approach as ";SnakeCut";, which is based on a probabilistic framework. To validate our approach, we show results both on simulated and natural images.
