Image and object detection method and system based on pre-classifier

一种基于预分类器的图像物体检测方法及系统

Abstract

The invention provides an object detection method based on a pre-classifier, which comprises the following steps: 1) calculating characteristics according to combination of bright-dark relations of pixel values in a plurality of local areas of a sample; 2) training the pre-classifier by the characteristics; and 3) detecting grayscale images by the pre-classifier, and performing posttreatment to obtain an object window. The method establishes the pre-classifier according to the characteristics of limited calculated amount and strong descriptive capacity, and pre-detects an object on the basis so as to effectively reduce false detection rate of object detection, improve the robustness of the object detection and obviously improve the speed of the object detection.
本发明提供一种基于预分类器的物体检测方法,包括下列步骤:1)根据样本的多个局部区域内像素值的亮暗关系的组合计算特征;2)利用所述特征训练预分类器;3)应用所述预分类器对灰度图像进行检测,并进行后处理,得到物体窗口。本发明根据计算量有限,且描述能力强的特征进行预分类器的构建,并依此进行物体预检测,从而有效降低了物体检测的误检率,提高了物体检测的鲁棒性,而且还显著提高了物体检测的速度。

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Cited By (7)

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