Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
On texture analysis: local energy transforms versus quadrature filters
Signal Processing
The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Advanced Methods in Neural Computing
Advanced Methods in Neural Computing
Texture Mixing and Texture Movie Synthesis Using Statistical Learning
IEEE Transactions on Visualization and Computer Graphics
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
International Journal of Human-Computer Studies
Content-Based Image Retrieval Incorporating Models of Human Perception
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Regression Modeling Strategies
Regression Modeling Strategies
Extensions of vector quantization for incremental clustering
Pattern Recognition
A genetic algorithm calibration method based on convergence due to genetic drift
Information Sciences: an International Journal
Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis
Information Sciences: an International Journal
A novel extended local-binary-pattern operator for texture analysis
Information Sciences: an International Journal
Evolving Vector Quantization for Classification of On-Line Data Streams
CIMCA '08 Proceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation
Texture as the basis for individual tree identification
Information Sciences: an International Journal
Automated vision system for localizing structural defects in textile fabrics
Pattern Recognition Letters
A Similarity Measure for Image and Volumetric Data Based on Hermann Weyl's Discrepancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Emotion-Based textile indexing using colors and texture
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
FLEXFIS: A Robust Incremental Learning Approach for Evolving Takagi–Sugeno Fuzzy Models
IEEE Transactions on Fuzzy Systems
An adaptable threshold detector
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
A genetic algorithm with the heuristic procedure to solve the multi-line layout problem
Computers and Industrial Engineering
Employing rough sets and association rule mining in KANSEI knowledge extraction
Information Sciences: an International Journal
Information Sciences: an International Journal
Texture analysis and classification: A complex network-based approach
Information Sciences: an International Journal
An interactive and flexible information visualization method
Information Sciences: an International Journal
Genetic algorithms supporting generative design of user interfaces: Examples
Information Sciences: an International Journal
Illumination-insensitive texture discrimination based on illumination compensation and enhancement
Information Sciences: an International Journal
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This paper deals with an approach allowing to associate visual textures with given human perceptions. Hereby, based on a forward model associating human perceptions for given visual textures, the deduction of an reverse process is presented which is able to associate and characterize visual textures for given human perceptions. For doing so, we propose a constraint-based genetic algorithm approach, which is able to minimize a specific optimization problem containing constraints in form of band-widths for valid individuals (low level features extracted from textures) in a population. The constraints are determined by relationships between (low level) features characterizing textures in form of high-dimensional approximation models. Additionally, in each iteration step checking for valid individuals is carried out with a texture/non-texture classifier or by using a convex hull over a set of valid textures. The whole approach is evaluated based on a real-world texture set used as a start population in the genetic algorithm and by defining various kinds of human perceptions (for which textures are sought) represented by adjective vectors in the aesthetic space. The generated individuals (low level feature vectors) have a high level of fitness (they are quite close to the pre-defined adjective vectors) and a small distance to the initial population. The textures synthesized based on the generated individuals are visualized and compared with textures synthesized by a time-intensive direct texture mixing and re-combination method based on a real-world texture data base.