TY - GEN
T1 - Detecting corners of polygonal and polyhedral objects
AU - Guo, Jinn Kwei
AU - Hsu, Rein Lien
AU - Chen, Chin Hsing
AU - Sun, Yung Nein
N1 - Publisher Copyright:
© 1993, Springer Verlag. All rights reserved.
PY - 1993
Y1 - 1993
N2 - In this paper, we proposed a novel corner detection algorithm, based on statistical properties of corners, to detect corners of both polygonal and polyhedral objects. By means of local histogram analysis, we first bilevel the subimage within a circular window, then compute the intensity mean for the bileveled subimage. From the intensity mean we can estimate the corner angle. We then calculate the theoretical position variance from the estimated angle. Comparing the position variance from the bileveled subimage with its theoretical value, we can identify whether or not the pixel at the center of the subimage is a corner. Finally, the corner orientation can be obtained from the position mean. Our algorithm can detect corners of both polygons and polyhedra, even if they appear in an image at the same time. It is superior to conventional detection algorithms that it can detect corners over a large range of angles.
AB - In this paper, we proposed a novel corner detection algorithm, based on statistical properties of corners, to detect corners of both polygonal and polyhedral objects. By means of local histogram analysis, we first bilevel the subimage within a circular window, then compute the intensity mean for the bileveled subimage. From the intensity mean we can estimate the corner angle. We then calculate the theoretical position variance from the estimated angle. Comparing the position variance from the bileveled subimage with its theoretical value, we can identify whether or not the pixel at the center of the subimage is a corner. Finally, the corner orientation can be obtained from the position mean. Our algorithm can detect corners of both polygons and polyhedra, even if they appear in an image at the same time. It is superior to conventional detection algorithms that it can detect corners over a large range of angles.
UR - https://www.scopus.com/pages/publications/85028888650
UR - https://www.scopus.com/pages/publications/85028888650#tab=citedBy
U2 - 10.1007/3-540-57233-3_32
DO - 10.1007/3-540-57233-3_32
M3 - Conference contribution
AN - SCOPUS:85028888650
SN - 9783540572336
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 237
EP - 244
BT - Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings
A2 - Chetverikov, Dmitry
A2 - Kropatsch, Walter G.
PB - Springer Verlag
T2 - 5th International Conference on Computer Analysis of Images and Patterns, CAIP 1993
Y2 - 13 September 1993 through 15 September 1993
ER -