TY - GEN
T1 - Elastic graph matching on gabor feature representation at low image resolution
AU - Sato, Yasuomi
AU - Kuriya, Yasutaka
PY - 2012/10/25
Y1 - 2012/10/25
N2 - We progressively improve conventional elastic graph matching (EGM) algorithm. In the conventional EGM, each node of a model graph can difficultly detect its corresponding precise position for the most similar Gabor feature extraction on an input low-resolution image. Solving this problem and then finding such a position, we propose a method that the node is allowed to fit among pixels by interpolating aliased Gabor feature representation between the pixels, which is calculated with the others extracted at the neighbor pixels. The model graph can thereby move to the most likely and more precise positions on the input low-resolution image.
AB - We progressively improve conventional elastic graph matching (EGM) algorithm. In the conventional EGM, each node of a model graph can difficultly detect its corresponding precise position for the most similar Gabor feature extraction on an input low-resolution image. Solving this problem and then finding such a position, we propose a method that the node is allowed to fit among pixels by interpolating aliased Gabor feature representation between the pixels, which is calculated with the others extracted at the neighbor pixels. The model graph can thereby move to the most likely and more precise positions on the input low-resolution image.
KW - Elastic Graph Matching
KW - Interpolation for Aliased Gabor Feature Representation
KW - Low Resolution Images
UR - http://www.scopus.com/inward/record.url?scp=84867689715&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867689715&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33269-2_49
DO - 10.1007/978-3-642-33269-2_49
M3 - Conference contribution
AN - SCOPUS:84867689715
SN - 9783642332685
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 387
EP - 394
BT - Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
T2 - 22nd International Conference on Artificial Neural Networks, ICANN 2012
Y2 - 11 September 2012 through 14 September 2012
ER -