Improved SIFT features in image retrieval using

摘要：

In this paper, based on SIFT feature algorithm, the SIFT feature descriptor is improved, the area of feature points used to construct a new circular region feature descriptor, thus improving the characteristics of the problem of high dimension, but also enhanced features descriptor of their own antirotation, and then two images by calculating the feature vector Euclidean distance, the findings were compared in order to achieve image matching, in building the image database to find the minimum distance vector with which to achieve the target image retrieval. Experimental results show that the algorithm not only has the scale, translation, rotation invariance, but also the use of more stable and faster image retrieval.

关键词： Image retrieval SIFT feature descriptor Image matching Euclidean distance

作者: Jie zhao Tingfang Xin Guozun Men

作者单位: College of Electronic and Information Engineering,Hebei University Baoding, China College of Electronics Hebei University Baoding, China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 393-397

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）