Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Handbook of pattern recognition & computer vision
Texture Segmentation Using Fractal Dimension
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Classification Using Windowed Fourier Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
From random walks to spin glasses
Proceedings of the 16th annual international conference of the Center for Nonlinear Studies on Landscape paradigms in physics and biology : concepts, structures and dynamics: concepts, structures and dynamics
Gabor wavelets for statistical pattern recognition
The handbook of brain theory and neural networks
Texture analysis and classification using deterministic tourist walk
Pattern Recognition
Deterministic tourist walks as an image analysis methodology based
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
An image analysis methodology based on deterministic tourist walks
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
Texture descriptor based on partially self-avoiding deterministic walker on networks
Expert Systems with Applications: An International Journal
Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks
Expert Systems with Applications: An International Journal
Dynamic texture segmentation based on deterministic partially self-avoiding walks
Computer Vision and Image Understanding
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Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology.