Shape recognition using eigenvalues of the Dirichlet Laplacian
Pattern Recognition
An evolutionary system for near-regular texture synthesis
Pattern Recognition
A fractal-based relaxation algorithm for shape from terrain image
Computer Vision and Image Understanding
Image and Vision Computing
Fabric defect detection based on multiple fractal features and support vector data description
Engineering Applications of Artificial Intelligence
An improved box-counting method for image fractal dimension estimation
Pattern Recognition
Object density-based image segmentation and its applications in biomedical image analysis
Computer Methods and Programs in Biomedicine
Multifractal signature estimation for textured image segmentation
Pattern Recognition Letters
Empirical mode decomposition synthesis of fractional processes in 1D- and 2D-space
Image and Vision Computing
Dimensionality in image analysis
Journal of Visual Communication and Image Representation
Coarse iris classification using box-counting to estimate fractal dimensions
Pattern Recognition
Two-channel nonseparable wavelets statistically matched to 2-D images
Signal Processing
Computers in Biology and Medicine
Fuzzy Hopfield neural network clustering for single-trial motor imagery EEG classification
Expert Systems with Applications: An International Journal
Color texture analysis based on fractal descriptors
Pattern Recognition
Ultrasonic liver tissue characterization by feature fusion
Expert Systems with Applications: An International Journal
How to Transform and Filter Images Using Iterated Function Systems
SIAM Journal on Imaging Sciences
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Multiscale Texture Extraction with Hierarchical (BV,Gp,L2) Decomposition
Journal of Mathematical Imaging and Vision
Illuminant invariant descriptors for color texture classification
CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging
Probabilistic pseudo-morphology for grayscale and color images
Pattern Recognition
Hi-index | 0.15 |
This paper addresses the problems of 1) representing natural shapes such as mountains, trees, and clouds, and 2) computing their description from image data. To solve these problems, we must be able to relate natural surfaces to their images; this requires a good model of natural surface shapes. Fractal functions are a good choice for modeling 3-D natural surfaces because 1) many physical processes produce a fractal surface shape, 2) fractals are widely used as a graphics tool for generating natural-looking shapes, and 3) a survey of natural imagery has shown that the 3-D fractal surface model, transformed by the image formation process, furnishes an accurate description of both textured and shaded image regions. The 3-D fractal model provides a characterization of 3-D surfaces and their images for which the appropriateness of the model is verifiable. Furthermore, this characterization is stable over transformations of scale and linear transforms of intensity. The 3-D fractal model has been successfully applied to the problems of 1) texture segmentation and classification, 2) estimation of 3-D shape information, and 3) distinguishing between perceptually ``smooth'' and perceptually ``textured'' surfaces in the scene.