Rotation invariant object recognition using gabor filters

Siddhaling Urolagin; K. V. Prema; N. V. Subba Reddy

doi:10.1109/ICIINFS.2010.5578669

Rotation invariant object recognition using gabor filters

Siddhaling Urolagin, K. V. Prema, N. V. Subba Reddy

Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	2010 5th International Conference on Industrial and Information Systems, ICIIS 2010
Pages	404-407
Number of pages	4
DOIs	https://doi.org/10.1109/ICIINFS.2010.5578669
Publication status	Published - 02-11-2010
Event	2010 5th International Conference on Industrial and Information Systems, ICIIS 2010 - Mangalore, Karnataka, India Duration: 29-07-2010 → 01-08-2010

Conference

Conference	2010 5th International Conference on Industrial and Information Systems, ICIIS 2010
Country/Territory	India
City	Mangalore, Karnataka
Period	29-07-10 → 01-08-10

All Science Journal Classification (ASJC) codes

Information Systems
Information Systems and Management
Industrial and Manufacturing Engineering

Access to Document

10.1109/ICIINFS.2010.5578669

Cite this

@inproceedings{ceacdb9a6e9845cabc6bf073cc6f4ee8,

title = "Rotation invariant object recognition using gabor filters",

abstract = "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.",

author = "Siddhaling Urolagin and Prema, {K. V.} and {Subba Reddy}, {N. V.}",

year = "2010",

month = nov,

day = "2",

doi = "10.1109/ICIINFS.2010.5578669",

language = "English",

isbn = "9781424466535",

pages = "404--407",

booktitle = "2010 5th International Conference on Industrial and Information Systems, ICIIS 2010",

note = "2010 5th International Conference on Industrial and Information Systems, ICIIS 2010 ; Conference date: 29-07-2010 Through 01-08-2010",

}

Urolagin, S, Prema, KV & Subba Reddy, NV 2010, Rotation invariant object recognition using gabor filters. in 2010 5th International Conference on Industrial and Information Systems, ICIIS 2010., 5578669, pp. 404-407, 2010 5th International Conference on Industrial and Information Systems, ICIIS 2010, Mangalore, Karnataka, India, 29-07-10. https://doi.org/10.1109/ICIINFS.2010.5578669

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.

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DO - 10.1109/ICIINFS.2010.5578669

M3 - Conference contribution

AN - SCOPUS:77958557477

SN - 9781424466535

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 -

Rotation invariant object recognition using gabor filters

Abstract

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