CBIR System with Scale-Invariant Feature Transform

• Main Authors: Ling-Hsuan Huang, 黃齡萱
• Other Authors: Wei-Ming Chen
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/30841024099347199111

碩士 === 國立宜蘭大學 === 資訊工程研究所碩士班 === 97 === These years, with the development of Multimedia System and Computer Network, the number of digital image grows rapidly. The thesis mentions that CBIR (Content-based Image Retrieval) System with Scale-Invariant Feature Transform and match the assistance of Artificial Neural Network, in order to achieve the accuracy and efficiency of retrieval. For solving Semantic Gap of Content-based Image Retrieval, in this part of image feature analysis, this thesis choose characteristics of color and texture and combine local gray-level variant to obtain keypoints; these characteristics are scale-invariant and the quality of unchangeable rotation, although it can search information of keypoints easilier compared by images of scale or variation of rotation and through these keypoints to reduce the difference of word meaning to promote the accuracy of system retrieval.