Content-based image retrieval using color and texture fused features

摘要：

This paper presents a method to extract color and texture features of an image quickly for contentbased image retrieval (CBIR). First, HSV color space is quantified rationally. Color histogram and texture features based on a co-occurrence matrix are extracted to form feature vectors. Then the characteristics of the global color histogram, local color histogram and texture features are compared and analyzed for CBIR. Based on these works, a CBIR system is designed using color and texture fused features by constructing weights of feature vectors. The relevant retrieval experiments show that the fused features retrieval brings better visual feeling than the single feature retrieval, which means better retrieval results.

关键词： Content based image retrieval HSV Color Texture

作者: Jun Yue Zhenbo Li Lu Liu Zetian Fu

作者单位: School of Information Science and Engineering. LUDONG University, YanTai, 264025, China College of I College of Information and ElectricalEngineering, China Agricultural University, Beijing, 100083, Ch College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, C

会议类型: 国际会议

会议名称: The 4th IFIP International on Computer and Computing Technologies in Agriculture and the 4th Symposium on Development of Rural Information(第四届国际计算机及计算机技术在农业中的应用研讨会暨第四届中国农业信息化发展论坛 CCTA 2010)

会议地点: 南昌

会议语种:英文

页码: 1121-1127

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）