Image Texture Feature Extraction Method Based on Regional Average Binary Gray Level Difference Co-occurrence Matrix

摘要：

Texture feature is a measure method about relationship among the pixels in local area,reflecting the changes of image space gray levels.This paper presents a texture feature extraction method based on regional average binary gray level difference co-occurrence matrix,which combined the texture structural analysis method with statistical method.Firstly,we calculate the average binary gray level difference of eight-neighbors of a pixel to get the average binary gray level difference image which expresses the variation pattern of the regional gray levels.Secondly,the regional co-occurrence matrix is constructed by using these average binary gray level differences.Finally,we extract the second-order statistic parameters reflecting the image texturefeature from the regional co-occurrence matrix.Theoretical analysis and experimental results show that the image texture feature extraction method has certain accuracy and validity.

关键词： texture feature average binary gray level difference regional co-occurrence matrix texture feature

作者: Jian Yang Jingfeng Guo

作者单位: College of Information Science and Engineering, Yanshan University Qinhuang dao, Hebei, China

会议类型: 国内会议

会议名称: 第十一届中国虚拟现实大会(ICVRV2011)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2011-11-04（万方平台首次上网日期，不代表论文的发表时间）