labelwatershed

在道路交通管理中，为了获得车辆的运动数据，早期经常采用的是感应线圈等硬件测量的方法。而如果采用摄像头拍摄的道路视频，再用计算机软件处理的方法，则可以极大的增加方便性和灵活性。本文运动目标检测与跟踪研究如何让计算机从视频图像序列中获得物体运动数据。(Traffic management in order to obtain motion data of the vehicle, is a method often used early induction coil measurement hardware. If using a video camera to shoot on the road, and then deal with methods of computer software, you can greatly increase the convenience and flexibility. This paper studies the moving target detection and tracking moving objects how to get data from a computer video image sequence.)

已知一个点到一条直线的距离，主要用在地图匹配中基于权重地图匹配算法中(Given a point to a straight line distance, mainly used in the map-matching weight based map-matching algorithm)

首次适应算法First Fit： 从空闲分区表的第一个表目起查找该表,把最先能够满足要求的空闲区分配给作业,这种方法目()

双目视觉 图像匹配 sift特征提取与匹配 极线校正(Binocular vision image matching sift feature extraction and matching polar line correction)

使用MATLAB语言实现简单的字符识别，使用神经网络算法，有效的识别车牌(Simple Character Recognition Using MATLAB Language)

说明：  在大图中寻找到小图。 并圈出小图所在位置。 图片用picture控件显示。(In the big picture to find a small map. )

shanChen两相流LBM的c版源代码，参考shanChen.m修改的，希望对不太熟悉Matlab的有所帮助(c code of liquid-liquid flow of shanchen)

UTIL MOTION DETECTION AND TRACKING

电压跌落是最严重的动态电能质量问题之一， 精确定位电压跌落起止时间是应对电压跌落问题的 重要前提和基础。由于电压采样信号往往有噪声分 量，现有的方法在定位电压跌落的起止时间时存在 局限性。本文提出利用多小波变换及相邻系数去噪 的电压跌落定位方法。多小波兼有对称性、正交性、 有限支撑性和二阶消失矩等优异的信号处理性能， 利用GHM多小波可以准确定位电压跌落起止时间。 多小波变换系数在每层之间具有对应关系，多小波 相邻系数将紧相邻的若干个系数作为一个整体来确 定阈值，考虑了系数之间的相关性，能获得更好的 去噪效果。通过 Matlab 进行仿真验证，仿真结果表 明，所提出的方法的正确性。 (Voltage sag is one of the most serious dynamic power quality problems. Critical start-time and end-time are important indices for voltage sags. But the sampling signals often have noisy component, the locations of start-time and end-time are hard to get. Wavelet is an effective tool for those non-stationary signal processing and has been used in this field. Local feature in the signal can be enlarged after the transformation using the scalar wavelet. But scalar wavelets cannot contain orthogonality, symmetry, compact support and higher order of vanishing moments simultaneously. In this thesis, multi-wavelets GHM is used to detect and locate power quality disturbances. Multi-wavelets offer many excellent properties such as the same approximation order but more compact support. The dependence of the multi-wavelets coefficients varies with the level, so neighboring coefficien)

可实现偏振图像合成以得到强度图像，偏振度图像等(Polarization image synthesis can be achieved to obtain intensity images, polarization images, etc.)