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2017 | OriginalPaper | Chapter

Multi-threshold Image Segmentation Method Based on Flower Pollination Algorithm

Authors : Jingjing Xue, Xingshi He, Xinshe Yang, Xiaoying Hao, Feiyue He

Published in: Bio-inspired Computing: Theories and Applications

Publisher: Springer Singapore

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Abstract

Multi-threshold segmentation is a powerful technique that is used for the processing of pattern recognition and computer vision. However, traditional, exhaustive search is computationally expensive when searching for thresholds. In order to solve such challenging problems, the fitness function is designed by the maximum entropy method, the optimal threshold of segmentation is found by using the parallel optimization mechanism of Flower Pollination algorithm (FPA), then a multi-threshold image segmentation algorithm based on FPA is proposed. The experimental results show that FPA is superior to the genetic algorithm (GA) and the shuffled frog leaping algorithm (SFLA).

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Metadata
Title
Multi-threshold Image Segmentation Method Based on Flower Pollination Algorithm
Authors
Jingjing Xue
Xingshi He
Xinshe Yang
Xiaoying Hao
Feiyue He
Copyright Year
2017
Publisher
Springer Singapore
Book
Bio-inspired Computing: Theories and Applications

Print ISBN: 978-981-10-7178-2

Electronic ISBN: 978-981-10-7179-9

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-7179-9_4

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