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利用模糊能量的纹理图像缺损区域自动定位

Automatic Locating of Defective Regions in Texture Image Using Fuzzy Energy

  • 摘要: 针对纹理图像中的信息缺失区域检测问题,提出一种由粗到精的缺损区域自动定位方法.在粗定位阶段,采用高斯滤波和阈值法去除背景纹理信息,以获取缺损区域初始粗边缘;在精确定位阶段,引入基于模糊能量的改进Chan-Vese主动轮廓模型,并以粗边缘作为模型演化的初始曲线,通过水平集方法实现对缺损区域的精确定位.实验结果表明,该方法可以实现对不同类型缺损区域的精确、自动定位,具有较高的计算效率和鲁棒性.

     

    Abstract: Aiming at detecting regions with missing information in texture image, a coarse-to-fine method is proposed to achieve the automatic locating of defective regions.In the coarse locating phase, Gaussian filtering and threshold segmentation are employed to remove background texture and acquire the rough contour of defects.In the precise positioning stage, an improved Chan-Vese active contours model based on fuzzy energy is introduced and the rough contour is taken as the initial curve for the model.During implementation, level set method is used to find the precise edges of defective regions. Experimental results show that our method is able to achieve accurate and automatic locating of different defective regions with high computational efficiency and robustness.

     

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