A concurrent modified algorithm for Generalized Hough Transform

T. Achalakul, S. Madarasmi
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引用次数: 6

Abstract

This paper presents a novel concurrent algorithm for object detection based on the Hough Transform. The Generalized Hough Transform can detect object contours regardless of scale and orientation, but has a computational complexity of O(N/sup 2/RS), where N, R, and S are the array dimensions for X/Y, rotation, and scale, respectively. The high complexity makes it impossible to perform object detection in real-time. In our work, we propose a modified, concurrent algorithm using a multi-threading technique with manager-worker scheme to obtain a reduced complexity of O(N/sup 2//M) where M is the number of processors. Our new algorithm utilizes multi-threading technology to enhance the computing speed. The algorithm is evaluated from both the perspective of output image quality and performance scalability.
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广义霍夫变换的并发改进算法
提出了一种基于霍夫变换的并行目标检测算法。广义霍夫变换可以不考虑尺度和方向检测物体轮廓,但计算复杂度为0 (N/sup 2/RS),其中N、R和S分别为X/Y、旋转和尺度的阵列维数。高复杂度使得实时目标检测成为不可能。在我们的工作中,我们提出了一种改进的并发算法,使用具有管理器-工作器方案的多线程技术来获得降低的复杂度为0 (N/sup 2//M),其中M是处理器的数量。我们的新算法利用多线程技术来提高计算速度。从输出图像质量和性能可扩展性两方面对算法进行了评价。
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