基于水平/垂直边缘的车辆检测算法

M. Boumediene, A. Ouamri, M. Keche
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引用次数: 10

摘要

提出了一种基于嵌入式视觉架构的驾驶辅助系统车辆检测算法。在生成假设之前,我们建议划分搜索区域。霍夫变换用于检测划分搜索区域的线。这样可以减少假设生成阶段的计算时间和误检率。搜索区域由霍夫变换确定,可在后续帧中跟踪。假设的生成基于水平边缘,由于保险杠,后窗,板等,并通过索贝尔滤波器检测。对假设的验证包括找到“U”形。为此,我们验证了两个垂直边的存在,左边和右边,每一个都连接到一个水平边。取得了令人满意的结果,在不同情况下的检测正确率达到90%,速率达到11帧/秒。该算法可在嵌入式DSP平台上实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle detection algorithm based on horizontal/vertical edges
This paper presents a vehicle detection algorithm for driver assistance system based on embedded vision architecture. Before generating the hypothesis, we propose to delimiter the search area. The Hough transform is used to detect the lines that delimit the search area. By doing so we can reduce the computation time and the false detection rate during the hypothesis generation phase. The search area is determined by the Hough transform and can be tracking in the following frames. The generation of hypothesis is based on horizontal edges, due to bumper, rear window, plate, etc. and detected by a Sobel filter. The verification of the hypothesis consists to find the “U” shape. For that we verify the presence of two vertical edges, left and right, each connected to a horizontal edge. Satisfactory results have been obtained, representing 90% of correct detection in different situations and with a good rate of 11 frame/s. The algorithm can be implemented on embedded DSP platform.
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