Novel and improved methods of regular geometric shape recognition from digital image using artificial ants

A. Acharya, K. Chattopadhyay, A. Banerjee, A. Konar
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引用次数: 0

Abstract

This contribution demonstrates how artificial ants can extract regular geometric shapes from grey scale images. We propose here two methods the first of which is a modified version of existing Ant System algorithm. The second method proposed is Ant Regeneration and Recombination System (ARRS). Our schemes comprise of three steps. Firstly, MATLAB edge detection operator converts a grey scale image into a binary one. Our schemes are then applied on this binary image to detect closed loops. Finally, these closed loops are tested for different geometric shapes. The schemes with incredible time and memory efficiency can detect both intersecting and non intersecting regular shapes.
基于人工蚂蚁的数字图像规则几何形状识别新方法
这一贡献展示了人工蚂蚁如何从灰度图像中提取规则的几何形状。我们在这里提出了两种方法,第一种是现有蚂蚁系统算法的修改版本。第二种方法是蚁群再生重组系统(ARRS)。我们的计划包括三个步骤。首先,利用MATLAB边缘检测算子将灰度图像转换为二值图像。然后将我们的方案应用于该二值图像以检测闭环。最后,对不同几何形状的闭环进行了测试。该方案具有令人难以置信的时间和存储效率,可以检测相交和非相交的规则形状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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