TY - GEN
T1 - Trellis-based circle detection
AU - Hild, Kenneth E.
AU - Erdogmus, Deniz
AU - Mathan, Santosh
AU - Pavel, Misha
PY - 2008
Y1 - 2008
N2 - We introduce a new method for finding circles in images. The proposed method assumes a given pixel is the center of a prospective circle, attempts to fit a circle at that location to the data, and then it scans over all possible pixels. The score at each assumed center location is found by traversing a trellis structure. The trellis allows for gaps in the prospective circles and it enforces a global all or none constraint. The proposed method is compared to a binary matched filter using real visible-spectrum aerial images, where the targets are the circular-shaped silos of surface-to-air missile sites. The proposed method perfonns noticeably better than the binary matched filter for the data used in this study.
AB - We introduce a new method for finding circles in images. The proposed method assumes a given pixel is the center of a prospective circle, attempts to fit a circle at that location to the data, and then it scans over all possible pixels. The score at each assumed center location is found by traversing a trellis structure. The trellis allows for gaps in the prospective circles and it enforces a global all or none constraint. The proposed method is compared to a binary matched filter using real visible-spectrum aerial images, where the targets are the circular-shaped silos of surface-to-air missile sites. The proposed method perfonns noticeably better than the binary matched filter for the data used in this study.
UR - http://www.scopus.com/inward/record.url?scp=58049181694&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=58049181694&partnerID=8YFLogxK
U2 - 10.1109/MLSP.2008.4685481
DO - 10.1109/MLSP.2008.4685481
M3 - Conference contribution
AN - SCOPUS:58049181694
SN - 9781424423767
T3 - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
SP - 211
EP - 215
BT - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
T2 - 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
Y2 - 16 October 2008 through 19 October 2008
ER -