Color texture analysis based on fractal descriptors

Authors:
André Ricardo Backes;Dalcimar Casanova;Odemir Martinez Bruno
Affiliations:
Faculdade de Computação, Universidade Federal de Uberlíndia, Av. João Naves de Ávila, 2121, 38408-100, Uberlíndia, MG, Brazil;Instituto de Física de São Carlos (IFSC), Universidade de São Paulo, Av. Trabalhador São Carlense, 400 13560-970 São Carlos, SP, Brazil;Instituto de Física de São Carlos (IFSC), Universidade de São Paulo, Av. Trabalhador São Carlense, 400 13560-970 São Carlos, SP, Brazil
Venue:
Pattern Recognition
Year:
2012

Citing 27
Cited 2

Structural Analysis of Natural Textures

IEEE Transactions on Pattern Analysis and Machine Intelligence
Applied multivariate statistical analysis

Applied multivariate statistical analysis
Texture description and segmentation through fractal geometry

Computer Vision, Graphics, and Image Processing
Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
Unsupervised texture segmentation using Gabor filters

Pattern Recognition
Texture analysis

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
Filtering for Texture Classification: A Comparative Study

IEEE Transactions on Pattern Analysis and Machine Intelligence
Gabor wavelets for statistical pattern recognition

The handbook of brain theory and neural networks
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns

IEEE Transactions on Pattern Analysis and Machine Intelligence
Histogram ratio features for color texture classification

Pattern Recognition Letters
Color texture measurement and segmentation

Signal Processing - Special section on content-based image and video retrieval
The Multifractal Structure of Contrast Changes in Natural Images: From Sharp Edges to Textures

Neural Computation
Spatial and spectral quaternionic approaches for colour images

Computer Vision and Image Understanding
A New Approach to Estimate Fractal Dimension of Texture Images

ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Rotation-invariant colour texture classification through multilayer CCR

Pattern Recognition Letters
Handbook of Texture Analysis

Handbook of Texture Analysis
Color spectral analysis for spatial structure characterization of textures in IHLS color space

Pattern Recognition
Choice of a pertinent color space for color texture characterization using parametric spectral analysis

Pattern Recognition
Multiple Resolution Texture Analysis and Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fractal-Based Description of Natural Scenes

IEEE Transactions on Pattern Analysis and Machine Intelligence
Extended fractal analysis for texture classification and segmentation

IEEE Transactions on Image Processing
Fractal Dimension of Color Fractal Images

IEEE Transactions on Image Processing
Inverse and approximation problem for two-dimensional fractal sets

IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames

IEEE Transactions on Image Processing

Multilayer graph cuts based unsupervised color-texture image segmentation using multivariate mixed student's t-distribution and regional credibility merging

Pattern Recognition
Illuminant invariant descriptors for color texture classification

CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging

Quantified Score

Hi-index	0.01

Visualization

Abstract

Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods.