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An efficient method for segmentation of images based on fractional calculus and natural selection

机译：一种基于分数演算和自然选择的有效图像分割方法

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摘要

Image segmentation has been widely used in document image analysis for extraction of printed characters, map processing in order to find lines, legends, and characters, topological features extraction for extraction of geographical information, and quality inspection of materials where defective parts must be delineated among many other applications. In image analysis, the efficient segmentation of images into meaningful objects is important for classification and object recognition. This paper presents two novel methods for segmentation of images based on the Fractional-Order Darwinian Particle Swarm Optimization {FODPSO) and Darwinian Particle Swarm Optimization {DPSO) for determining the n-1 optimal n-level threshold on a given image. The efficiency of the proposed methods is compared with other well-known thresholding segmentation methods. Experimental results show that the proposed methods perform better than other methods when considering a number of different measures.
机译：图像分割已广泛用于文档图像分析中，以提取印刷字符，进行地图处理以找到线条，图例和字符，提取拓扑特征以提取地理信息以及必须在其中划定缺陷部分的材料进行质量检查。许多其他应用程序。在图像分析中，将图像有效分割成有意义的对象对于分类和对象识别很重要。本文提出了两种基于分数阶达尔文粒子群优化算法（FODPSO）和达尔文粒子群优化算法（DPSO）的图像分割方法，用于确定给定图像的n-1个最佳n级阈值。所提出的方法的效率与其他众所周知的阈值分割方法进行了比较。实验结果表明，在考虑多种不同措施的情况下，所提方法的性能优于其他方法。

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  • 来源
    《Expert Systems with Application》 |2012年第16期|p.12407-12417|共11页
  • 作者

    Pedram Ghamisi; Micael S. Couceiro; Jon Atli Benediktsson; Nuno M.F. Ferreira;

  • 作者单位

    Geodesy & Geomatics Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran,No. 11, Fotouhi St., Farabi St., Ardakani St.,Guyabadi St., Zafar St., Shariati st. Tehran, Iran Postal code: 1916759333;

    Institute of Systems and Robotics, University of Coimbra, Polo II, 3030-290 Coimbra, Portugal,RoboCorp at the Electrical Engineering Department, Engineering Institute of Coimbra, Rua Pedro Nunes - Quinta da Nora, 3030-199 Coimbra, Portugal;

    Faculty of Electrical and Computer Engineering, University of Iceland, Saemundargotu 2, 101 Reykjavik, Iceland;

    RoboCorp at the Electrical Engineering Department, Engineering Institute of Coimbra, Rua Pedro Nunes - Quinta da Nora, 3030-199 Coimbra, Portugal,GECAD - Knowledge Engineering and Decision Support Research Center Institute of Engineering, Polytechnic of Porto (ISEP/IPP) Porto, Portugal;

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  • 正文语种 eng
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  • 关键词

    multilevel segmentation; swarm optimization; image processing;

    机译：多层次细分群优化;图像处理;

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