Titlebook: Applications of Evolutionary Computation in Image Processing and Pattern Recognition; Erik Cuevas,Daniel Zaldívar,Marco Perez-Cisneros Boo

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Image Segmentation Based on Differential Evolution Optimization,tion (DE) is a heuristic method for solving complex optimization problems, yielding promising results. DE is easy to use, keeps a simple structure and holds acceptable convergence properties and robustness. In this chapter, an automatic image multi-threshold approach based on differential evolution

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Template Matching by Using the States of Matter Algorithm,and remote sensing. The TM approach seeks the best possible resemblance between a sub-image, known as template, and its coincident region within a source image. TM has two critical aspects: similarity measurement and search strategy. The simplest available TM method finds the best possible coinciden

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Automatic Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms,orithms based on evolutionary principles have been successfully applied to image segmentation with interesting performances. However, most of them maintain two important limitations: (1) they frequently obtain sub-optimal results (misclassifications) as a consequence of an inappropriate balance betw

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