基于Hough变换的自上而下人脸识别

Y. He, Yiqun Huang, Zhibiao Li
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引用次数: 0

摘要

霍夫变换具有边缘不完全识别的优点。大量的实践表明:对于实际的圆形物体检测,检测点通常集中在一个相对连续的圆弧内。如果检测点分散在圆的各个位置,通常是噪声的干扰导致目标的错误识别。在此基础上,本文提出了一种算法,即计算检测到的边缘点角度的标准差,并将标准差值与检测到的边缘点进行比较,从而判断对圆形物体的识别是否正确。本文将该算法应用于人脸识别,取得了良好的效果。
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Recognize Human Head Shot Top Down Based on Hough Transform
Hough transform has the advantage of incomplete edge recognition. A large number of practices show that: for the actual circular object detection, the detected points are usually concentrated in a relatively continuous arc. If the detected points are scattered in various positions of the circle, it is usually the interference of noise that causes the wrong recognition of the target. On this basis, this paper proposes an algorithm, that is, to calculate the standard deviation of the angle of the detected edge points, and compare the standard deviation value with the detected edge points, so as to judge whether the recognition of the circular object is correct. In this paper, the algorithm is applied to human head recognition and good results are obtained.
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