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A Novel Image Segmentation Algorithm Based on Active Contour Model and Retinex Model

Published: 24 January 2020 Publication History

Abstract

The algorithm of active contour model is an image segmentation method based on curve evolution theory, which have great flexibility, adaptability and separation accuracy. Accurate segmentation of inhomogeneous image targets has always been a difficult issue in image segmentation field. In this paper, an improved Chan-Vese model based on local information is proposed, which utilizes both global and local image information. Combining the local binary fitting (LBF) model with the retinex model, this paper redefines the fit of the Chan-Vese model. And adding a weight coefficient, so that the fitting term adaptively calculates the respective weights of the global and local information. The experimental results on various image data show that the proposed method can achieve more accurate segmentation results.

References

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  1. A Novel Image Segmentation Algorithm Based on Active Contour Model and Retinex Model

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    ICAIP '19: Proceedings of the 2019 3rd International Conference on Advances in Image Processing
    November 2019
    232 pages
    ISBN:9781450376754
    DOI:10.1145/3373419
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 24 January 2020

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    Author Tags

    1. Active contour model
    2. CV model
    3. LBF model
    4. image segmentation
    5. retinex model

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