An Active Contour Model Driven By the Hybrid Signed Pressure Function

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1. Verfasser: Zhao, Jing
Format: Preprint
Veröffentlicht: 2024
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author Zhao, Jing
author_facet Zhao, Jing
contents Due to the influence of imaging equipment and complex imaging environments, most images in daily life have features of intensity inhomogeneity and noise. Therefore, many scholars have designed many image segmentation algorithms to address these issues. Among them, the active contour model is one of the most effective image segmentation algorithms.This paper proposes an active contour model driven by the hybrid signed pressure function that combines global and local information construction. Firstly, a new global region-based signed pressure function is introduced by combining the average intensity of the inner and outer regions of the curve with the median intensity of the inner region of the evolution curve. Then, the paper uses the energy differences between the inner and outer regions of the curve in the local region to design the signed pressure function of the local term. Combine the two SPF function to obtain a new signed pressure function and get the evolution equation of the new model. Finally, experiments and numerical analysis show that the model has excellent segmentation performance for both intensity inhomogeneous images and noisy images.
format Preprint
id arxiv_https___arxiv_org_abs_2403_07570
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An Active Contour Model Driven By the Hybrid Signed Pressure Function
Zhao, Jing
Computer Vision and Pattern Recognition
Numerical Analysis
Due to the influence of imaging equipment and complex imaging environments, most images in daily life have features of intensity inhomogeneity and noise. Therefore, many scholars have designed many image segmentation algorithms to address these issues. Among them, the active contour model is one of the most effective image segmentation algorithms.This paper proposes an active contour model driven by the hybrid signed pressure function that combines global and local information construction. Firstly, a new global region-based signed pressure function is introduced by combining the average intensity of the inner and outer regions of the curve with the median intensity of the inner region of the evolution curve. Then, the paper uses the energy differences between the inner and outer regions of the curve in the local region to design the signed pressure function of the local term. Combine the two SPF function to obtain a new signed pressure function and get the evolution equation of the new model. Finally, experiments and numerical analysis show that the model has excellent segmentation performance for both intensity inhomogeneous images and noisy images.
title An Active Contour Model Driven By the Hybrid Signed Pressure Function
topic Computer Vision and Pattern Recognition
Numerical Analysis
url https://arxiv.org/abs/2403.07570