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Technical Program
Paper Detail
| Paper: | WA-P1.11 |
| Session: | Image and Video Segmentation |
| Time: | Wednesday, October 11, 09:40 - 12:20 |
| Presentation: |
Poster
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| Title: |
TEXTURED IMAGE SEGMENTATION BASED ON SPATIAL DEPENDENCE USING A MARKOV RANDOM FIELD MODEL |
| Authors: |
William Schwartz; University of Maryland | | | | | Hélio Pedrini; Federal University of Parana | | |
| Abstract: |
Image segmentation is a primary step in many computer vision tasks. Although many segmentation methods have been proposed in the last decades, there is no generic method that can be applied in a great variety of images. This work presents a new image segmentation method using texture features extracted by wavelet transforms combined with spatial dependence modeled by a Markov random field (MRF). The method initially produces a coarse segmentation, which is refined through a relaxation method based on a new energy function. A set of textured images is used to demonstrate the effectiveness of the proposed method. |
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