Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gabor wavelets for statistical pattern recognition
The handbook of brain theory and neural networks
Picture Processing and Psychopictorics
Picture Processing and Psychopictorics
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
2D Euclidean distance transform algorithms: A comparative survey
ACM Computing Surveys (CSUR)
Plant leaf identification using Gabor wavelets
International Journal of Imaging Systems and Technology
Comparison of texture features based on Gabor filters
IEEE Transactions on Image Processing
Design-based texture feature fusion using Gabor filters and co-occurrence probabilities
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Gabor wavelets combined with volumetric fractal dimension applied to texture analysis
Pattern Recognition Letters
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Texture plays an important role on image analysis and computer vision. Local spatial variations of intensity and color indicate significant differences among several types of surfaces. One of the most widely adopted algorithms for texture analysis is the Gabor wavelets. This technique provides a multi-scale and multi-orientation representation of an image which is capable of characterizing different patterns of texture effectively. However, the texture descriptors used does not take full advantage of the richness of detail from the Gabor images generated in this process. In this paper, we propose a new method for extracting features of the Gabor wavelets space using volumetric fractal dimension. The results obtained in experimentation demonstrate that this method outperforms earlier proposed methods for Gabor space feature extraction and creates a more accurate and reliable method for texture analysis and classification.