Application of Cuckoo Search Algorithm for Image Segmentation

Kaouter Labed, H. Fizazi, H. Mahi
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Abstract

Image analysis has a large interest in remote sensing, it is used for extract pertinent information, and the segmentation is found at the bottom of each analysis. Image segmentation is also considered as one of the most difficult, critical and essential tasks in image processing. It determines the quality of the final analysis result. Image segmentation can be viewed as an optimization problem, Meta heuristic optimization methods and in particular bio-inspired methods are very used in image segmentation, they can be applied to any mono or multiobjective optimization problem. In this paper we present a meta heuristic approach based on Cuckoo Search Algorithm (CSA) for the purpose of solving the problem of image segmentation in general and in particularly the satellite images segmentation.
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杜鹃搜索算法在图像分割中的应用
图像分析在遥感中有很大的兴趣,它用于提取相关信息,并且在每次分析的底部找到分割。图像分割也被认为是图像处理中最困难、最关键和最基本的任务之一。它决定了最终分析结果的质量。图像分割可以看作是一个优化问题,元启发式优化方法,特别是生物启发方法在图像分割中非常常用,它们可以应用于任何单目标或多目标优化问题。本文提出了一种基于布谷鸟搜索算法(CSA)的元启发式方法,用于解决一般图像分割问题,特别是卫星图像分割问题。
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