车载异构非制冷红外成像行人检测系统

车载红外夜间行人检测具有重要的实用价值,传统系统往往结构复杂、行人检测算法实时性难以保证。针对该问题提出了基于FPGA + DaVinci处理器构架的非制冷红外热成像行人检测系统,充分利用红外焦平面的成像特点,获取经预处理后的图像画质清晰；在检测行人区域过程中,提出结合局部自适应阈值分割和形态学处理的预处理方法,能够有效去除强背景的干扰；另外,利用Haar-like特征事先训练AdaBoost分类器,进行ROI的分类、识别。实验结果表明,采用多核心异构的系统,具备结构紧凑、数据通信难度小、算法移植性强等优势；FPGA对算法加速效果约为38 %,实时检测帧频达到了25 f/s。

Vehicle-mounted heterogeneous uncooled infrared imaging pedestrian detection system

Night-vehicle-mounted infrared pedestrian detection is of great value.It was found that the traditional system is always complicated in structure,and the real-time performance of the pedestrian detection algorithm is difficult to guarantee.To overcome this problem,an uncooled infrared thermal imaging pedestrian detection system based on the FPGA & Davinci-device architecture was presented.High quality preprocessed images can be obtained with the rational use of infrared focal plane.During the ROI isolation,the methods of local adaptive threshold segmentation and morphological process were used to remove the interference of strong background.In addition,the algorithm differentiated the candidate regions with AdaBoost classifier,which was trained with Haar-like features.Experimental results show that the multi-core heterogeneous system has the advantages including compact structure,low data communication difficulty,and strong algorithm portability;FPGA accelerates the algorithm by about 38 %,and it performs in real-time at a rate of 25 f/s.