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Proceedings of the 6th ACM international conference on Image and video retrieval
Simplified Gabor wavelets for human face recognition
Pattern Recognition
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CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Recycled paper visual indexing for quality control
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Complex wavelet transform-based face recognition
EURASIP Journal on Advances in Signal Processing
Gabor feature constrained statistical model for efficient landmark localization and face recognition
Pattern Recognition Letters
Image and Vision Computing
A Multi-Scale Algorithm for Graffito Advertisement Detection from Images of Real Estate
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
Object class detection using local image features and point pattern matching constellation search
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Object tracking on FPGA-based smart cameras using local oriented energy and phase features
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
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Image and Vision Computing
Topological Gabor descriptors: exploring a filter bank structure for image feature matching
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
A local spectral distribution approach to face recognition
Computer Vision and Image Understanding
Finger-vein ROI localization and vein ridge enhancement
Pattern Recognition Letters
Reliable Face Recognition Using Artificial Neural Network
International Journal of System Dynamics Applications
Multi-resolution feature fusion for face recognition
Pattern Recognition
Two-dimensional multi-pixel anisotropic Gaussian filter for edge-line segment (ELS) detection
Image and Vision Computing
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Information Sciences: an International Journal
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For almost three decades the use of features based on Gabor filters has been promoted for their useful properties in image processing. The most important properties are related to invariance to illumination, rotation, scale, and translation. These properties are based on the fact that they are all parameters of Gabor filters themselves. This is especially useful in feature extraction, where Gabor filters have succeeded in many applications, from texture analysis to iris and face recognition. This study provides an overview of Gabor filters in image processing, a short literature survey of the most significant results, and establishes invariance properties and restrictions to the use of Gabor filters in feature extraction. Results are demonstrated by application examples.