文章基本信息

标题：Image type-based Assessment of SIFT and FAST Algorithms
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作者：Muthukrishnan R ; Ravi J
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：3
页码：211-216
DOI：10.14257/ijsip.2015.8.3.19
出版社：SERSC
摘要：Identifying the interest points in an image is a key step in image processing and computer vision tasks. Every corner of the images represents a lot of information. Extracting the true corners is the main object to image processing, which can reduce much of the time and calculations. Many algorithms have been suggested in the image processing to detect the true corners, based on the robust statistics. In this paper the corner detection algorithms SIFT and FAST have been studied in image processing under the various image formats. Also, it can provide a direction to the researchers to use the algorithm for the suitable image format and to develop a new algorithm which can detect the exact corners of an image/blurred image. The FAST corner detection method compared with the results of SIFT corner detection method. Experimental results show that the FAST corner detection gives better results compared to SIFT method. All the experiments are carried out MATLAB software
关键词：Corner detection; SIFT; FAST; robust features