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The Research of Leather image segmentation Using Texture analysis Techniques

机译:用纹理分析技术研究皮革图像分割

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The leather productions are produced rapidly in people's living, the productions' quality is required stricter. Leather must be detected include leather plainness;;leather surface defects and the density of leather before they are produced to be productions.. The most important aspect is the surface defects;;the defects' location, size and quantity should be confirmed. One of the most important steps of leather defects detection is leather image segmentation so as to extract leather defects. Gray level co-occurrence matrix is used to extract a lot of leather surface texture feature, the method of optimized Fuzzy C-means is used to segment leather image in the article. The optimized Fuzzy C-means add the spatial information;;the precision of segmentation is improved. The image needs to be treated use morphological approach after it is segmented. As a result, the defective areas are separated from non-defective areas successfully.
机译:皮革制作在人们的生活中迅速生产,产品质量是更严格的。 必须检测到皮革,包括皮革平整;;皮革表面缺陷和皮革密度在生产之前是制作的。最重要的方面是表面缺陷;缺陷的位置,尺寸和数量应该确认。 皮革缺陷检测的最重要步骤之一是皮革图像分割,以提取皮革缺陷。 灰度级共发生矩阵用于提取大量皮革表面纹理特征,优化的模糊C-Meance方法用于分割制品中的皮革图像。 优化的模糊C均值添加空间信息;;分割的精度得到改善。 在分段后,需要处理图像使用形态学。 结果,缺陷区域成功地与非缺陷区域分离。

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