| Paper: | IMDSP-L1.6 | ||
| Session: | Image and Video Analysis | ||
| Time: | Wednesday, May 19, 14:40 - 15:00 | ||
| Presentation: | Lecture | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Analysis | ||
| Title: | SHAPE GRADIENT FOR IMAGE SEGMENTATION USING INFORMATION THEORY | ||
| Authors: | Ariane Herbulot; I3S Laboratory | ||
| Stephanie Jehan Besson; I3S Laboratory | |||
| Michel Barlaud; I3S Laboratory | |||
| Gilles Aubert; Dieudonne Laboratory | |||
| Abstract: | This paper deals with video and image segmentation using region based active contours. We consider the problem of segmentation through the minimization of a new criterion based on information theory. We first propose to derive a general criterion based on the probability density function using the notion of shape gradient. This general derivation is then applied to criterions based on information theory, such as the entropy or the conditional entropy for the segmentation of sequences of images. We present some experimental results on grayscale images and color videos showing the perfomance of the proposed method. | ||
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