A study on the Algorithm Based on Image Color Correlation Mining

摘要：

Because of the semantic gap between low-level feature and high-level semantic feature of images, the results of the traditional color-based image retrieval cant meet usersneeds. In order to eliminate interference factors in the image retrieval, use image semantic feature and improve the accuracy of image retrieval, the paper introduces an algorithm based on the color correlation mining. It regards the pixel rows as a transaction set, uses the Apriori algorithm to find out the rows by looking for the continual co-occurrence color in the transaction set. These rows are correlative with the semantic object of the image. Then it extracts the correlative color histogram of image form the correlative color set to realize the correlative color mining.

作者: Chen Yongyue Xia Huosong

作者单位: Department of Information Management and Information System,Wuhan University of Science & Engineering,Wuhan,China

会议类型: 国际会议

会议名称: The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

会议地点: 西安

会议语种:英文

页码: 377-380

在线出版日期: 2009-08-18（万方平台首次上网日期，不代表论文的发表时间）