Fundamentals of digital image processing
Fundamentals of digital image processing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Graphical Models and Point Pattern Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
An algorithm for projective point matching in the presence of spurious points
Pattern Recognition
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Information Sciences: an International Journal
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
Evolutionary programming using mutations based on the Levy probability distribution
IEEE Transactions on Evolutionary Computation
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
An Evolutionary Algorithm for Global Optimization Based on Level-Set Evolution and Latin Squares
IEEE Transactions on Evolutionary Computation
An evolutionary tabu search for cell image segmentation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic design of biologically inspired receptive fields for neural pattern recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hybridization of fuzzy GBML approaches for pattern classification problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Hybrid evolutionary algorithms are drawing significant attention in recent time for solving numerous real world problems. This paper presents a new hybrid evolutionary approach for optimizing mathematical functions and Point Pattern Recognition (PPR) problems. The proposed method combines a global search genetic algorithm in a course-to-fine resolution space with a local (Tabu) search algorithm. Such hybridization enhances the power of the search technique by virtue of inducing hill climbing and fast searching capabilities of Tabu search process. The approach can reach the global or near-global optimum for the functions in high dimensional space. Tests have been successfully made on several benchmark functions in up-to 100 dimensions. The performance of the proposed algorithm has been compared with other relevant algorithms using non-parametric statistical approaches like Friedman test, multiple sign-test and contrast estimation. Also, the hybrid method with grid based PPR technique has been applied for solving dot pattern shape matching and object matching represented as edge maps. The performance of proposed method compares favorably with relevant approaches reported in the article.