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Symmetry
Volume 14
Issue 11
10.3390/sym14112343
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Article

An Active Contour Model Based on Retinex and Pre-Fitting Reflectance for Fast Image Segmentation

by
Chengxin Yang
,
Lele Wu
,
Yiyang Chen
*,
Guina Wang
and
Guirong Weng
*
School of Mechanical and Electric Engineering, Soochow University, Suzhou 215137, China
*
Authors to whom correspondence should be addressed.
Symmetry 2022, 14(11), 2343; https://doi.org/10.3390/sym14112343
Submission received: 29 September 2022 / Revised: 31 October 2022 / Accepted: 5 November 2022 / Published: 7 November 2022
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Abstract

In the present article, this paper provides a method for fast image segmentation for computer vision, which is based on a level set method. One dominating challenge in image segmentation is uneven illumination and inhomogeneous intensity, which are caused by the position of a light source or convex surface. This paper proposes a variational model based on the Retinex theory. To be specific, firstly, this paper figures out the pre-fitting reflectance by using an algorithm in the whole image domain before iterations; secondly, it reconstructs the image domain using an additive model; thirdly, it uses the deviation between the global domain and low-frequency component to approximate the reflectance, which is the significant part of an energy function. In addition, a new regularization term has been put forward to extract the vanishing gradients. Furthermore, the new regularization term is capable of accelerating the segmentation process. Symmetry plays an essential role in constructing the energy function and figuring out the gradient flow of the level set.
Keywords: inhomogeneous intensity; active contour model; image segmentation; retinex theory; LoG algorithm inhomogeneous intensity; active contour model; image segmentation; retinex theory; LoG algorithm

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MDPI and ACS Style

Yang, C.; Wu, L.; Chen, Y.; Wang, G.; Weng, G. An Active Contour Model Based on Retinex and Pre-Fitting Reflectance for Fast Image Segmentation. Symmetry 2022, 14, 2343. https://doi.org/10.3390/sym14112343

AMA Style

Yang C, Wu L, Chen Y, Wang G, Weng G. An Active Contour Model Based on Retinex and Pre-Fitting Reflectance for Fast Image Segmentation. Symmetry. 2022; 14(11):2343. https://doi.org/10.3390/sym14112343

Chicago/Turabian Style

Yang, Chengxin, Lele Wu, Yiyang Chen, Guina Wang, and Guirong Weng. 2022. "An Active Contour Model Based on Retinex and Pre-Fitting Reflectance for Fast Image Segmentation" Symmetry 14, no. 11: 2343. https://doi.org/10.3390/sym14112343

APA Style

Yang, C., Wu, L., Chen, Y., Wang, G., & Weng, G. (2022). An Active Contour Model Based on Retinex and Pre-Fitting Reflectance for Fast Image Segmentation. Symmetry, 14(11), 2343. https://doi.org/10.3390/sym14112343

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