CameraFingerprint

交通视频车辆检测，实现步骤为： 1.读取视频文件 2.利用图像提取相关算法检测单帧图像中的车辆 3.车辆检测算法应用于视频图像中 4.将结果可视化(Traffic video vehicle detection, the steps of: 1. Read the video file 2. Image extracting the vehicle in a single image of the correlation algorithm detecting vehicle detection algorithm applied to the video image. Results visualization)

对故障信号进行去噪，自己调试的程序，带注释(The fault signal to denoise, debug their own procedures, with notes)

关于图像小波边缘检测的MATLAB程序，用于一般图像边缘检测(wavelet-edge)

用偏微分方法进行图像修复，可以修复灰度和彩色图像(By partial differential method for image restoration, can repair gray and color images)

matlab 中的视频图像处理。可用的程序()

主要是一个小的图像处理程序,是将一个模糊的图像进行复原的程序(It is mainly a small image processing program.)

用于图像配准，角点提取后采用相关系数法进行特征匹配(For image registration, corner detection using correlation coefficient method after the feature matching)

ENVI中HDF5科学数据支持补丁,更新为一个SAV文件 ,放在安装目录的save_add文件 夹下，启动ENVI即可使用。(HDF5 scientific data in support of ENVI patches, updates to a SAV file on the installation directory save_add folder, start ENVI can be used.)

视觉slam十四讲，程序资料：g2o优化、cere拟合、特征点提取与匹配、点云拼接、opencv图像读取(Visual slam 14, program data: g2o optimization, cere fitting, feature point extraction and matching, point cloud mosaic, OpenCV image reading)

针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )