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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >A new computation of shape moments via quadtree decomposition
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A new computation of shape moments via quadtree decomposition

机译:四叉树分解的形状矩新计算

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摘要

The main contribution of this paper is in designing an optimal and/or optimal speed-up algorithm for computing shape moments. We introduce a new technique for computing shape moments. The new technique is based on the quadtree representation of images. We decompose the image into a number of non-overlapped squares, since the moment computation of squares is easier than that of the whole image. The proposed sequential algorithm reduces the computational complexity significantly. By integrating the advantages of both optical transmission and electronic computation, the proposed parallel algorithm can be run in O(1) time using N x N1+1/c processors when the input image is complicated, if the input image is simple (i.e., the image can be represented by a few quadtree nodes), the proposed parallel algorithm can be run in O(1) time using N x N processors. In the sense of the product of time and the number of processors used, the proposed parallel algorithm is time and cost optimal and achieves optimal speed-up. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 41]
机译:本文的主要贡献在于设计用于计算形状矩的最佳和/或最佳加速算法。我们介绍了一种计算形状矩的新技术。新技术基于图像的四叉树表示。我们将图像分解为多个非重叠的正方形,因为正方形的矩计算比整个图像的矩计算容易。所提出的顺序算法显着降低了计算复杂度。通过整合光传输和电子计算的优势,如果输入图像很简单(例如,输入图像很简单),则可以使用N x N1 + 1 / c处理器在O(1)时间内运行提出的并行算法。图像可以由几个四叉树节点表示),建议的并行算法可以使用N x N个处理器在O(1)时间内运行。从时间和使用的处理器数量的乘积的意义上讲,所提出的并行算法是时间和成本最优的,并且可以实现最佳的加速。 (C)2001模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:41]

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