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Decomposition of binary morphological structuring elements based on genetic algorithms

机译:基于遗传算法的二元形态结构元素分解

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Most image processing architectures adapted to morphological operations use structuring elements of a limited size. Various algorithms have been developed for decomposing a large sized structuring element into dilations of small structuring components. However, these decompositions often come with certain restricted conditions. In this paper, we present an improved technique using genetic algorithms to decompose arbitrarily shaped binary structuring elements. The specific initial population, fitness functions, dynamic threshold adaptation, and the recursive size reduction strategy are our features to enhance the performance of decomposition. It can generate the solution in less computational costs, and is suited for parallel implementation. (c) 2005 Elsevier Inc. All rights reserved.
机译:适用于形态学运算的大多数图像处理体系结构都使用有限大小的结构元素。已经开发了各种算法来将大型结构元素分解为小的结构部件的膨胀。但是,这些分解通常带有某些受限条件。在本文中,我们提出了一种使用遗传算法对任意形状的二进制结构元素进行分解的改进技术。特定的初始种群,适应度函数,动态阈值自适应和递归大小缩减策略是我们增强分解性能的功能。它可以以较少的计算成本生成解决方案,并且适合于并行实施。 (c)2005 Elsevier Inc.保留所有权利。

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