资源列表
super-resolution
- 通过Matlab与Java混合编程的超分辨率处理的源代码，采用插值的方法，能较好地实现超分辨率处理。-A method of super-resolution by interpolation witch can solve a image.
FrameSubContourTrack
- 使用OPENCV,对交通视频，做帧间差及外轮廓提取跟踪,内包含测试视频数据，测试时，放于D盘根目录。-Using OPENCV, of traffic video, do and outer contour extraction tracking, frame difference contained within the test video data, test, put in D packing list.
OpenCV_ru-men
- 该书短小精悍，适合对Opencv进行入门学习时使用，若要对OpenCV进行快速学习也可参考此书。-The book dapper, suitable for getting started Opencv use, quick to learn of OpenCV can refer to the book.
OpenCV_study_ji_chu
- 本书是国内第一本全面介绍OpenCV的中文版图书，本书可作为信息、图像处理和模式识别等领域的高年级本科生、研究生使用，也可作为研发人员的参考手册。-This book is the first comprehensive introduction to OpenCV s Chinese version of the book, this book can be used as information, image processing and pattern recognition in are
tuxiangfenge
- emgu环境下的分水岭算法实现，可以研究研究-Watershed algorithm on c#
OpticalFlowOri
- 基于opencv的光流法源码，主要应用为目标跟踪，会给出目标运动角点的起始位置与当前位置的连线-Connection opencv source code based on optical flow method, the main application for the target tracking, target motion corners will give the starting position and the current position
MyOpenCVCammer
- 基于OPENCV3.0的颜色识别，容易移植。-Based on the OPENCV3.0 color recognition
pf_soccer
- VS2012，opencv3.0的基于颜色特征的粒子滤波跟踪算法实现，代码比较直观，虽然效率较慢，但容易理解。可直接运行-particle filter in object tracking ,based on color feature vs2012+opencv3.0
Face-Recognition
- 非匀速运动模糊光照和姿态人脸识别，英文文献-Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose
openCV-binarization
- 将一幅彩色图像二值化为灰度图像，其中灰度值大于某一阈值的像素赋予灰度值1，小于该阈值的像素赋予灰度值0-A color image to a grayscale image binarized, wherein the gray value is greater than a threshold value assigned to the pixel gray value 1, is smaller than the threshold value assigned to the pixel g
SIFT-RANSAC
- opencv里的SIFT检测与RANSAC提纯，具备RANSC算法的详细步骤,VS2010环境-opencv in the SIFT and RANSAC to detect purified with RANSAC algorithm detailed steps
histram
- 用于相似颜色图像检索，传统直方图法，巴氏系数法，传统欧式距离法-For the image similarity graph, the traditional histogram Bhattacharyya coefficient method, traditional Euclidean distance method