为了实现威胁源自动报警,使用BP神经网络构建自动报警系统.针对帧差法提取出的目标轮廓有重复和受变化背景影响的问题,提出了一种基于轮廓片段的目标特征提取方法.首先使用k-mediod聚类以剔除重复轮廓,再结合轮廓片段生长的方法,计算待识别轮廓和验证图片集的匹配代价以剔除背景轮廓,提取出匹配代价最小的轮廓生成轮廓片段字典.随后计算归一化的轮廓矩生成特征向量.最后将提取出的特征向量输入事先训练生成的BP神经网络进行分类.实验结果表明,算法适用于典型刚性目标识别,对于实验视频中枪支的平均识别率达到93.5％,单帧平均运算时间3.67 ms；对于Berkeley运动分割数据集中车辆的识别率达到98.2％,单帧平均运算时间5.26 ms.算法具有高实时性、高准确率的特点.
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