应用区域颜色分割的机采棉杂质检测方法  

Detection method for machine-harvested cotton impurities based on region color segmentation

作　　者：张成梁[1] 李蕾[2] 董全成[1] 葛荣雨[1] 

机构地区：[1]济南大学机械工程学院,山东济南250022 [2]齐鲁工业大学机械与汽车工程学院,山东济南250353

出　　处：《纺织学报》2017年第7期135-141,共7页Journal of Textile Research

基　　金：国家自然科学基金项目(51305164;51405194);山东省重点研发计划项目(2016GNC110025)

摘　　要：机采棉中的杂质繁杂,而杂质类型及含量对后期棉花加工工艺的影响很大。为此,提出一种应用区域颜色分割方法以检测棉花中的杂质。在图像分割中,先对滤波后的机采棉图像进行彩色梯度运算,通过扩展极小变换运算获得标记图像,在修改后的梯度图像上运用分水岭算法获得初始分割图像,然后对初始分割图像进行区域合并。区域合并过程中要综合考虑空间邻接性、颜色信息和区域面积3个因素。颜色信息主要采用饱和度、亮度、区域颜色向量模及颜色相似度4个特征量。用层次递进的合并方法,迭代过程更新信息特征。最后通过支持向量机算法提取颜色、纹理、形状特征对杂质区域进行识别。结果表明,所提方法对机采棉中天然杂质的平均识别率为94%。Machine-harvested cotton impurities are complicated. It is important to detect the type and content of impurities for adjustment of the processing technique of cotton. An impurity detection method based on region color segmentation was presented. During image segmentation stage color gradient image was obtained based on filtered image firstly. Marking image was achieved by H-minima transform,and initial segmentation image was acquired based on modified gradient image by watershed algorithm. Then region merging was conducted for initial segmentation image. Region adjacency,region color feature and region area were considered for region merging. Region color features such as saturation,intensity,region color vector module and color similarity were used. Repeated merging was adopted, and information of color feature was updated in different merging. Finally various features including color,texture and shape were extracted by support vector machines algorithm for impurity recognition.Experimental results show that a successful recognition ratio of 94% for natural impurities is achieved.

关 键 词：机采棉 图像分割 杂质识别 标记分水岭 区域合并 颜色特征 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]