Abstract
This paper describes a novel approach to extract object region from an image by tracking the enclosing contour. We assume that the image is not complex, and it can be roughly partitioned into two parts with an intensity threshold. A lot of images (for example medical images) are in accord with this assumption. Global constraint (threshold) and local constraint (gradient) are integrated in a particle filter framework. We utilize the filter to track the optimal contour path pixel by pixel. The processing time depends only on the contour length and the number of particles used. Thus the proposed method is significantly faster than the very popular and time consuming method: Active Contour Models (“Snakes”). Both Snakes and our method are targeted for similar applications. Experimental results illustrate the validity and advantages of our method.
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Lu, C., Latecki, L.J., Zhu, G. (2008). Contour Extraction Using Particle Filters. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_19
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DOI: https://doi.org/10.1007/978-3-540-89646-3_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89645-6
Online ISBN: 978-3-540-89646-3
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