提出一种自动识别人体边缘物体的算法, 用于太赫兹人体安检系统的人体边缘物体成像的识别。原始图像经过二值化、滤波除噪、填充、形态学腐蚀膨胀等预处理算法后, 利用顺时针搜寻轮廓追踪算法标记图像轮廓坐标, 对轮廓上各坐标点使用圆形模板占空比检测以及非极小、非极大值抑制算法筛选出所有的凸点和凹点, 并根据相邻凸点和凹点组合特征及其横向距离约束实现边缘物体的识别。500幅测试图像实验结果表明: 该算法对边缘物体可实现快速识别, 误判率在2%以下; 通过调整算法参数, 可良好匹配安检系统的识别精度, 从而达到匹配于系统的分辨极限; 具有抗噪声能力强, 识别速度快, 识别精度高等优点。

An automatic recognition algorithm was proposed for recognizing objects concealed on the edge of human body in an image, which was scanned by THz human security system. First, the pretreatment methods, with binarization, filtering, filling, and morphological corrosion and expansion operations, were used to transfer the original THz image into a binary image, whose outline coordinates was later extracted by clockwise contour tracking algorithm. Then, the combinative application of circular template detection and non-minimal, non-maxima suppression algorithm were applied to calculate and select out all the convex and concave points in the extracted profile coordinates. Finally based on the grouping features of these adjacent convex and concave points, together with their distance constraints, the recognition of the edge objects(Objects covered the contour of human, etc.) could be realized. The experimental results, of testing 500 images of different people with different objects hiding on different edge position taking by the THz human security system, show that this algorithm represents quick identification and strong robustness, having the distinct advantages of strong anti-noise ability, high recognition speed and precision, and also it can match well the recognition accuracy of security system to achieve the system′s resolution limit by adjusting proper parameters of the algorithm.