可重构网格上的凸性问题

Chia-Long Lee, Wen-Tsuen Chen
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引用次数: 0

摘要

可重构网格是一种具有总线自治的并行系统,可以在算法执行过程中支持多种互连方案。它在许多应用领域提供了非常高效的计算能力。在数字图像处理和计算机视觉中,凸性是图像空间中物体的自然形状描述符和分类器。我们首先提出了在可重构网格上凸包极值点的识别问题可以在O(1)时间内解决。此外,我们提出了一些可重构网格上的凸性相关问题的常数时间算法。这些问题包括点包含、内部检测、面积和凸包宽度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Convexity problems on reconfigurable meshes
The reconfigurable mesh, a parallel system with bus autonomy, can support various interconnection schemes during execution of an algorithm. It offers very efficient computation power in many application domains. In digital image processing and computer vision, convexity is a natural shape descriptor and a classifier for objects in the image space. We first present that the problem of identifying extreme points of convex hulls can be solved in O(1) time on the reconfigurable mesh proposed. Furthermore, we present constant time algorithms for a number of convexity-related problems on reconfigurable meshes. These problems include point inclusion, interior detection, area, and width of convex hulls.
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