TY - GEN
T1 - Rotation invariant object recognition using gabor filters
AU - Urolagin, Siddhaling
AU - Prema, K. V.
AU - Subba Reddy, N. V.
PY - 2010/11/2
Y1 - 2010/11/2
N2 - In recent years, Gabor filters have found effective for feature extraction as they possess many properties such as tunable to specific orientation, spectrally localized, spatially localized etc. In this paper, a rotation invariant object recognition system is proposed using Gabor filters. A set of Gabor filters are considered and directional features are extracted from an image. A Gabor Vector Set is created from an unknown image sample, which may be rotated. A combined classification approach using K-Nearest Neighbor classifier and Minimum distance classifier is developed to predict the class label of the unknown sample. Experiments are conducted on electric component images which are rotated between 0° to 360° angle. An overall recognition rate of 96.02% is observed on database of size 3971 images.
AB - In recent years, Gabor filters have found effective for feature extraction as they possess many properties such as tunable to specific orientation, spectrally localized, spatially localized etc. In this paper, a rotation invariant object recognition system is proposed using Gabor filters. A set of Gabor filters are considered and directional features are extracted from an image. A Gabor Vector Set is created from an unknown image sample, which may be rotated. A combined classification approach using K-Nearest Neighbor classifier and Minimum distance classifier is developed to predict the class label of the unknown sample. Experiments are conducted on electric component images which are rotated between 0° to 360° angle. An overall recognition rate of 96.02% is observed on database of size 3971 images.
UR - https://www.scopus.com/pages/publications/77958557477
UR - https://www.scopus.com/inward/citedby.url?scp=77958557477&partnerID=8YFLogxK
U2 - 10.1109/ICIINFS.2010.5578669
DO - 10.1109/ICIINFS.2010.5578669
M3 - Conference contribution
AN - SCOPUS:77958557477
SN - 9781424466535
T3 - 2010 5th International Conference on Industrial and Information Systems, ICIIS 2010
SP - 404
EP - 407
BT - 2010 5th International Conference on Industrial and Information Systems, ICIIS 2010
T2 - 2010 5th International Conference on Industrial and Information Systems, ICIIS 2010
Y2 - 29 July 2010 through 1 August 2010
ER -