Multi-scale curvature based image corner detection and matching
Corners are important local features of image. Corner detection and matching techniques play important roles in image understanding and computer vision. The paper proposes a new adaptive corner detection method based on multi-scale curvature representation. First, the contour of the image is extracted by the Canny edge detection technique. The curvature of each point in the contour is calculated at a high scale in Gaussian multi-scale space and the points with local maximum of values of curvature are obtained. An adaptive block technology is proposed to determine candidate corners. Then, the accurate locations of the corners are determined at a low scale level. In order to match corners in images of distinct views, the gradient histogram of neighborhood region around each corner is constructed to determine a principal orientation. A corner matching algorithm based on principal orientation and gray correlation is proposed. Experimental results show that both of new algorithms are stable, reliable, and efficient.
Corner detection Corner matching Multi-scale curvature Principal orientation
Tingquan Deng JinXu
Department of College of Science The University of Harbin Engineering Harbin, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
946-949
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）