The fast Fourier transform and its applications
The fast Fourier transform and its applications
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Texturing and modeling: a procedural approach
Texturing and modeling: a procedural approach
Texture Segmentation Using Fractal Dimension
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing
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
Texture classification using multiresolution Markov random field models
Pattern Recognition Letters
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Digital Image Processing
Evaluation of the effects of Gabor filter parameters on texture classification
Pattern Recognition
Fractal dimension applied to plant identification
Information Sciences: an International Journal
MultiWaveMed: a system for medical image retrieval through wavelets transformations
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
Retrieval by content of medical images using texture for tissue identification
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
Optimal Gabor filters for texture segmentation
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
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Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.