Aimed at the characteristics of low deviation between targets and background and weak boundaries,a novel approach of fast convergence and strong ability to capture boundaries was presented based on level set method. We used index function with quicker convergence as indicator function and normalized Gauss distribution function to improve traditional Dirac function. In the tracking process of the moving target, this article obtained minimum circumscribed rectangular frames of human moving target in every video frame with the kalman filter method, and used the method of the level set curve evolution to obtain moving human target outline eventually. Experiments on targets under the visible light and infrared moving video sequences show this method can greatly improve the tracking speed compared with traditional methods and has better results in target-tracking and contour extraction for infrared images with weak boundaries and huge convexandconcave features.%针对图像中目标和背景灰度偏差较小、目标边缘轮廓弱的特点,提出了一种快速收敛并具有较强捕获弱边缘能力的水平集曲线演化方法.该方法采用指数函数作为边缘指示函数,运用归一化的Gauss分布函数改进传统的正则化Dirac函数.在目标跟踪过程中,采用卡尔曼滤波获取视频相应帧图像的运动人体目标最小外接矩形框,对外接矩形框内运动人体进行水平集曲线演化,实现对人体目标的跟踪和轮廓提取.分别对可见光下的运动目标和红外运动视频序列进行仿真实验.结果表明,相对于传统方法,其在跟踪速度上有很大的提高,对于红外图像中的弱边界目标及凸凹度较大的区域,也具有快速准确的收敛效果.
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