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Radius based cellular automata approach for image processing applications

机译:基于半径的元胞自动机方法在图像处理中的应用

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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.
机译:本文确定了一种基于细胞自动机的模型,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有关的活动,例如图像斑点,物体边缘,物体脊的检测,并提高输入图像或已处理图像的质量。所有应用程序都使用附近的邻居来达到目的。通过平均和微积分法,所有相邻像素均以半径形式划分,并且根据半径邻域累积阈值。阈值是实现该目标的共同因素。为了开发RBCA模型,使用了基于网格的概念,例如所有必需的数据都以网格或单元的形式排列。 RBCA方法的目标是代表转换函数将当前像元值更改为新像元值,并且转换函数以不超过2个半径像元值的目标为目标来生成新值。所有应用的实验结果表明了该方法的有效性。

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