摘要
为解决纬编针织物图像中灯光阴影、纤维脱散等干扰项对细化的影响,提出对纬编织物图像采取标准欧氏距离的K均值聚类分割算法进行降噪除杂。根据图像细化需要,对比分析查表细化法和Hilditch算法细化法对纬编针织物图像细化的效果。找出细化后产生并线、毛刺问题的原因,给出具体调整、修正此类问题的方法,并通过试验证实纬编针织物图像细化中的并线、毛刺等问题有良好的修复效果。
In order to solve the impact of light shadow and hairiness disturbances when thinning the weft knit- ting fabric image, this paper proposes the application of K-means clustering segmentation algorithm for noise reduc- tion and removing impurity. According to the requirements of the image, it comparatively analyzes the weft knitted fabric image refinement effect of the Hilditch thinning and the index table thinning. Besides, it finds out the rea- sons of doubling line and burr, and offers the way of eliminating the problem. Then its validity and feasibility are proved by experiment.
出处
《针织工业》
2016年第12期56-59,共4页
Knitting Industries
关键词
纬编针织物
图像细化
自动识别
K值聚类分割
Hilditch算法
查表细化
Weft Knitted Fabric
Image Thinning
Automatic Identification
K-means Clustering Segmentation
Hilditch Algorithm
Index Table Thinning
