DocumentCode :
2727710
Title :
On the Robustness of a New Boundary-Based Corner Detection Algorithm
Author :
Wen-Bing Horng ; Chun-Wen Chen ; Chen-Hsiang Chen
Author_Institution :
Dept. of Comput. Sci., Tamkang Univ. Taipei, Taipei, Taiwan
fYear :
2012
fDate :
16-18 Nov. 2012
Firstpage :
193
Lastpage :
198
Abstract :
Corners play an important role in computer vision, such as curve fitting, optical inspection, image segmentation, object recognition, etc. In our previous work, we proposed a new boundary-based corner detection algorithm. In this paper, we will compare it with other methods by conducting a rigorous experiment to evaluate the performances of both the curvature measurement and the optimization procedure. The experimental results are rather promising, they show that our new algorithm outperforms other algorithms.
Keywords :
computer vision; curvature measurement; edge detection; boundary-based corner detection algorithm; computer vision; curvature measurement; curve fitting; image segmentation; object recognition; optical inspection; optimization procedure; robustness; Covariance matrix; Detection algorithms; Eigenvalues and eigenfunctions; Noise; Optimization; Robustness; Shape; corner detection; curvature measurement; optimization method; robustneness; threshold estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technologies and Applications of Artificial Intelligence (TAAI), 2012 Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4673-4976-5
Type :
conf
DOI :
10.1109/TAAI.2012.45
Filename :
6395029
Link To Document :
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