期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2012
卷号：3
期号：5
页码：29
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Object recognition is an important task in image processing and computer vision. This paper presents aperfect method for object recognition with full boundary detection by combining affine scale invariantfeature transform (ASIFT) and a region merging algorithm. ASIFT is a fully affine invariant algorithm thatmeans features are invariant to six affine parameters namely translation (2 parameters), zoom, rotationand two camera axis orientations. The features are very reliable and give us strong keypoints that can beused for matching between different images of an object. We trained an object in several images withdifferent aspects for finding best keypoints of it. Then, a robust region merging algorithm is used torecognize and detect the object with full boundary in the other images based on ASIFT keypoints and asimilarity measure for merging regions in the image. Experimental results show that the presented methodis very efficient and powerful to recognize the object and detect it with high accuracy.
关键词：Object recognition; keypoint; affine invariant; region merging algorithm; ASIFT.
