What is it about?
Image segmentation is an important step in image processing, but contemporary segmentation algorithms have problems such as poor anti-noise performance, over-segmentation, and imprecise results. To solve these problems, in this paper, we proposed an adaptive image segmentation algorithm under the constraint of Edge Posterior Probability. Experiments showed that the proposed algorithm has excellent anti-noise performance, highly precise segmentation result, and are useful in effectively segmenting low-contrast images.
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Why is it important?
Image segmentation is an important step in image processing. In this paper, we proposed an adaptive image segmentation algorithm under the constraint of Edge Posterior Probability. It can effectively solve the problems such as poor anti-noise performance, over-segmentation, and imprecise results.
Perspectives
Image segmentation technology is a hot research area but also a highly difficult one. We proposed an adaptive image segmentation algorithm under the constraint of Edge Posterior Probability to solve the problems such as poor anti-noise performance, over-segmentation, and imprecise results, and it has achieved better results compared with other segmentation algorithms. I think it is an improvement in image segmentation.
Darling Dar
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This page is a summary of: Adaptive image segmentation algorithm under the constraint of edge posterior probability , IET Computer Vision, December 2017, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-cvi.2016.0213.
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