Radius based cellular automata approach for image processing applications

Sandeep Kumar Sharma, C. S. Lamba, V S Rathore
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引用次数: 5

Abstract

This paper ascertains a model based on cellular automata for implementing various applications relevant to image processing. This model can estimate various image relevant activities like detection of image blobs, edgesof objects, ridges of objects and improve the quality of input image or processed image. All the applications used nearby neighbors to achieve the objective. All the neighbor pixels are divided in the form of radius and a threshold value is accumulating according to the radius neighborhood by averaging and differential calculus method. The threshold value is a common factor to accomplish the objective. To develop RBCA model used grid based concept like all the necessary data are arranged in the form of grid or cell. Objective of RBCA method is to change the current cell value into new cell value on the behalf of transition function and the transition function target up to 2 radius cell value to generate new value. The experimental results of all the applications express efficiency of proposed method.
基于半径的细胞自动机方法在图像处理中的应用
本文确定了一种基于元胞自动机的模型,用于实现与图像处理相关的各种应用。该模型可以估计各种与图像相关的活动,如图像斑点、物体边缘、物体脊线的检测,提高输入图像或处理后图像的质量。所有的应用程序都使用附近的邻居来实现目标。将所有相邻像素以半径的形式进行分割,并通过平均和微分法根据半径邻域累积阈值。阈值是实现目标的常见因素。在开发RBCA模型时,采用了基于网格的概念,将所有必要的数据以网格或单元格的形式排列。RBCA方法的目标是将当前单元格值转换为代表过渡函数的新单元格值,过渡函数以2个半径范围内的单元格值为目标生成新值。所有应用的实验结果都表明了该方法的有效性。
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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