基于多参数Gabor滤波器融合和高斯差分的生丝疵点分割OACSTPCD
Segmentation of raw silk defects based on multi-parameter Gabor filter fusion and difference of Gaussian
针对生丝疵点图像背景与疵点差别极小的特点,提出一种基于多方向、多频率Gabor滤波器融合和高斯差分滤波的疵点分割算法.根据疵点纹理特性,首先采用极大值的方法对特定频率多方向疵点Gabor滤波图像进行融合,并基于均值法对不同频率Gabor滤波器图像进行融合,然后使用高斯差分滤波进一步凸显疵点,最后采用全局阈值将疵点与背景分割开来.测试结果表明:该研究算法召回率达到了93.2%,能够准确分割出生丝疵点.
In view of the small difference between background and defects of raw silk image,defect segmentation algorithm was proposed based on multi-directional and multi-frequency Gabor filter fusion and difference of Gaussian filter.According to the texture characteristics of defects,first of all,multi-directional defect Gabor filter images with specific frequency was fused based on maximum method.Gabor filter images with different frequencies were fused based on me…查看全部>>
杨言语;李子印;汪小东;叶飞;姚晓娟;金君;曾凡高
中国计量大学,浙江杭州,310018中国计量大学,浙江杭州,310018湖州市质量技术监督检测研究院,浙江湖州,313099湖州市质量技术监督检测研究院,浙江湖州,313099湖州市质量技术监督检测研究院,浙江湖州,313099湖州市质量技术监督检测研究院,浙江湖州,313099中国计量大学,浙江杭州,310018
轻工业
生丝疵点分割多参数融合Gabor滤波器高斯差分全局阈值分割
raw silk defect segmentationmulti-parameter fusionGabor filterdifference of Gaussianglobal threshold segmentation
《棉纺织技术》 2024 (6)
63-68,6
浙江省市场监督管理局青年科技项目(QN2023446)国家市场监督管理总局科技计划项目(2022MK048)浙江省基础公益研究计划项目(LGN20F50001)
评论