一种模糊特征驱动曲线演化的图像分割

石澄贤; 王洪元; 夏德深

doi:10.11834/jig.20100808

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专辑

一种模糊特征驱动曲线演化的图像分割
A Fuzzy Feature Driving Curve Evolution for Image Segmentation
2010年15卷第8期页码：1196
网络出版：2010-08-25，

纸质出版：2010
DOI： 10.11834/jig.20100808
稿件说明：

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石澄贤, 王洪元, 夏德深. 一种模糊特征驱动曲线演化的图像分割[J]. 中国图象图形学报, 2010,15(8):1196. DOI： 10.11834/jig.20100808.

SHI Chengxian, WANG Hongyuan, XIA Deshen. A Fuzzy Feature Driving Curve Evolution for Image Segmentation[J]. Journal of Image and Graphics, 2010, 15(8): 1196. DOI： 10.11834/jig.20100808.

摘要

利用模糊特征向量表示图像上各区域上的特性，然后把模糊特征向量集成到简化Mumford-Shah模型。这种推广的Mumford-Shah模型与原来的Mumford-Shah模型相比能包含更多的图像信息，增强了图像分割的性能，而复杂程度却没有提高。原来的模型是推广模型的特例。对弱边缘、凹凸区域和复杂背景的图像能较好地分割。人工合成图像、真实图像的实验说明推广模型对图像分割的有效性。

Abstract

Fuzzy feature vector has been used to represent the characteristics of image on different regions. The fuzzy feature vector has been integrated into Mumford-Shah model for the image segmentation. The generalized Mumford-Shah model has contained more information of image

enhanced capability of segmentation image and not increased complexity in comparison with original model. The original model is a particular case of the generalized model. The generalized model provides well segmentation to weak edges， concavo-convex region and complexity background image. Experimental results of applying the scheme to artificial and real images demonstrate its segmentation power.