Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Retinal vision applied to facial features detection and face authentication
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Fundamental Frequency Gabor Filters for Object Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Optimal Gabor Filters for High Speed Face Identification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Improving the SIFT descriptor with smooth derivative filters
Pattern Recognition Letters
Kernel Based Multi-object Tracking Using Gabor Functions Embedded in a Region Covariance Matrix
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
A computational-intelligence-based approach for detection of exudates in diabetic retinopathy images
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Recent advances in face biometrics with Gabor wavelets: A review
Pattern Recognition Letters
A kernel particle filter multi-object tracking using Gabor-based region covariance matrices
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Selecting optimal orientations of Gabor wavelet filters for facial image analysis
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Recognition of tire tread patterns based on Gabor wavelets and support vector machine
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part III
Model based selection and classification of local features for recognition using gabor filters
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
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Some recent works have addressed the object recognition problem by representing objects as the composition of independent image parts, where each part is modeled with “low-level” features. One of the problems to address is the choice of the low-level features to appropriately describe the individual image parts. Several feature types have been proposed, like edges, corners, ridges, Gaussian derivatives, Gabor features, etc. Often features are selected independently of the object to represent and have fixed parameters. In this work we use Gabor features and describe a method to select feature parameters suited to the particular object considered. We propose a method based on the Information Diagram concept, where “good” parameters are the ones that optimize the filter's response in the filter parameter space. We propose and compare some concrete methodologies to choose the Gabor feature parameters, and illustrate the performance of the method in the detection of facial parts like eyes, noses and mouths. We show also the rotation invariance and robustness to small scale changes of the proposed Gabor feature.