Fast, Multi-Scale Image Processing on a Square Spiral Framework

J. Fegan, S. Coleman, D. Kerr, B. Scotney
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Abstract

Efficient processing of digital images is a key consideration in many machine vision tasks. Traditional image processing approaches often struggle to meet this demand, particularly at the initial low-level of processing image pixels. To overcome this, we propose a spiral based processing approach which takes inspiration from the asymmetric lattice of interlocking cells found in the human visual system. Here we demonstrate the efficiency of the proposed spiral approach for multi-scale feature extraction. This is complemented by a biologically inspired image acquisition process which is used to capture nine image frames at different spatial locations. The results demonstrate that the biologically inspired spiral approach offers a faster alternative to corresponding traditional image processing approaches.
基于方形螺旋框架的快速多尺度图像处理
数字图像的有效处理是许多机器视觉任务的关键考虑因素。传统的图像处理方法往往难以满足这种需求,特别是在处理图像像素的初始低级。为了克服这一点,我们提出了一种基于螺旋的处理方法,该方法的灵感来自于人类视觉系统中发现的互锁细胞的不对称晶格。在这里,我们证明了所提出的螺旋方法在多尺度特征提取中的有效性。这是一个生物学启发的图像采集过程的补充,用于在不同的空间位置捕获九个图像帧。结果表明,生物学启发的螺旋方法提供了一种更快的替代相应的传统图像处理方法。
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