DocumentCode :
3045485
Title :
Steady corner detection for calibration in underwater environment
Author :
Guoliang, Yang ; Fuyuan, Peng ; Kun, Zhao
Author_Institution :
Electron. & Inf. Eng., Dept., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2010
fDate :
8-10 June 2010
Firstpage :
97
Lastpage :
100
Abstract :
Meanshift algorithm has been widely used in the fields of image filtering, image segmentation and object tracking. This article tries using Meanshift algorithm in corner detection. For camera calibration in the underwater environment, the article proposed a corner detection method based on Harris corner detection and Meanshift algorithm. First, calculate the Harris corner and the dot product between the shift vector and gradient vector of the underwater chessboard image, and combine the two characteristics to generate the probability density of right-angle corner measure, then take the Harris corner as the initial value, use the Meanshift algorithm to calculate high-precision corner locations and identify the false corners to remove them. The results of experiments show that the algorithm can achieve sub-pixel precision, and is suitable for calibration of underwater camera.
Keywords :
calibration; cameras; edge detection; probability; underwater equipment; Harris corner detection; corner detection method; dot product; high-precision corner locations; image filtering; image segmentation; meanshift algorithm; object tracking; probability density; right-angle corner measure; shift vector; steady corner detection; sub-pixel precision; underwater camera calibration; underwater chessboard image; underwater environment calibration; Calibration; Cameras; Feature extraction; Image edge detection; Image segmentation; Noise; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Control in Aeronautics and Astronautics (ISSCAA), 2010 3rd International Symposium on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-6043-4
Electronic_ISBN :
978-1-4244-7505-6
Type :
conf
DOI :
10.1109/ISSCAA.2010.5633353
Filename :
5633353
Link To Document :
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