Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Fuzzy System Design Principles
Fuzzy System Design Principles
Texture Segmentation using 2-D Gabor Elementary Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary localization in texture segmentation
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Texture is an important clue in region-based segmentation of images. Robust rotation and scale-invariant texture are important for digital image libraries and multimedia databases. Texture feature extraction operators, which comprise linear filtering followed by postprocessing, are considered. The CMF (Circular Mellin Feature) represents the spectral decomposition of the image scene in the polar-log coordinate system and is invariant to both scale and orientation of the target texture pattern. CMFs are used for rotation and scale-invariant texture classification. The image and CMFs are correlated, due to which the unique shift invariance property of the correlator architecture is also coupled. CMFs are based on log polar coordinate system. In this paper we present Real coded Genetic Algorithm (RcGA) for the parameter selection of CMFs. The simple genetic algorithm (GA) is search algorithms based on the mechanics of natural selection and genetics. It involves copying and swapping partial strings of data. A modified genetic algorithm is the RcGA, which basically employs real value vectors for representation of the chromosomes, and is widely applied to many optimization problems.