Image segmentation by minimum cross entropy using evolutionary methods

The segmentation of digital images is one of the most important steps in an image processing or computer vision system. It helps to classify the pixels in different regions according to their intensity level. Several segmentation techniques have been proposed, and some of them use complex operators....

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Vydané v:	Soft computing (Berlin, Germany) Ročník 23; číslo 2; s. 431 - 450
Hlavní autori:	Oliva, Diego, Hinojosa, Salvador, Osuna-Enciso, Valentín, Cuevas, Erik, Pérez-Cisneros, Marco, Sanchez-Ante, Gildardo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2019 Springer Nature B.V
Predmet:	Accuracy Algorithms Artificial Intelligence Complexity Computational Intelligence Computer vision Control Convergence Digital imaging Electromagnetism Engineering Entropy Entropy (Information theory) Evolutionary algorithms Image processing Image segmentation Mathematical Logic and Foundations Mechatronics Methodologies and Application Methods Optimization Pixels Robotics Thresholds Vision systems Electromagnetism optimization Cross entropy Evolutionary algorithms Image processing Segmentation
ISSN:	1432-7643, 1433-7479
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