example

对复杂边缘检测的Snake改进算法.pdf，snake算法(Complex Snake improved edge detection algorithm. Pdf, snake algorithm)

ASIFT算法实现，C++,对有仿射变换的图像匹配更加准确，想比SIFT算子匹配点数多(ASIFT algorithm, C++, affine transformation of the image matching more accurate, want to match more than SIFT operator points)

该程序是我多年的经验总结以及代码，实现了全景目标跟踪、火焰识别、烟雾识别、起立坐下行为判断、越界闯入、徘徊、违规停车等多种智能功能一体化，粒子滤波、贝叶斯分类器、随机森林等多种在线学习机制，还有传统的camshift、meanshift、光流法、卡尔曼滤波、struck、KCF、TLD、CT、区域匹配，相位相关、轮廓跟踪等多种算法(The program is my many years of experience and code, the realization of the panorama target tracking, flame detection, smoke detection, standing up sitting judge, cross-border intrusion, wandering, illegal parking and other various intelligent functions integration, particle filter, Bayesian classifier, random forest variety of online learning mechanism, and the traditional CAMSHIFT, meanshift, optical flow method, Kalman filter, the, KCF, regional matching, phase correlation, contour tracking and other several algorithms)

刚才传的所有程序试验处理的图像(passed the test procedures to deal with all the images)

针对目前工业制造领域面临的难题,提出利用非量测数字摄像机进行工业钣金件高精度三维重建与视觉检测.采用二维直接线性变换分解摄像机参数初值并结合光束法平差进行高精度标定 利用最小二乘模板匹配提取像面上的点、直线信息并进行混合光束法平差,从而进行钣金件的高精度三维重建及其尺寸制造误差的检测.所开发的视觉检测系统硬件成本低、自动化程度较高,实际数据的多次实验均取得了优于1/8 000的相对精度,说明所论述的方法为工业零件的自动化三维检测提供了一条可行途径.(View of the current challenges facing the field of industrial manufacturing, made use of non-metric digital camera precision sheet metal parts for industrial reconstruction and visual inspection. Using two-dimensional direct linear transformation and the decomposition of initial parameters of the camera bundle adjustment with high accuracy calibration extracted by the least square template matching, like the surface of point, line information and mixed bundle adjustment to the three-dimensional reconstruction of high-precision sheet metal parts and the size of the detection of manufacturing errors. visual inspection system developed by the hardware low cost, high degree of automation, the actual data, many experiments have achieved better than 1/8000 of the relative accuracy, that the methods discussed in the automation of industrial components to provide a feasible three-dimensional detection approach.)

图像取对数运算，很有帮助 (Images taken of the number of calculations, useful)

本书可作为信息处理、计算机、机器人、人工智能、遥感图像处理、认知神经科学等有关专业的高年级学生或研究生的教学用书，也可供相关领域的研究工作者参考。(This book can be used as information processing, computer, robot, remote sensing image processing, artificial intelligence, cognitive neuroscience and related professional senior student or graduate student s teaching resources, also can be used for reference in the related areas of research workers.)

对深度图像进行滤波、渲染和着色，更加可视化(depth image visualition and filtering for coming 3D reconstruction)

说明：  对三角划分算法的研究，对以前方法的改进，以达到良好的效果，(Triangulation algorithm to study the improvement of previous methods in order to achieve good results,)

横断面数据抬杆法格式与中心点为原点格式格式转换 高程加常数(Cross-sectional data raise the center pole method format format format converter for the origin plus constant elevation)