About a .OpenCV
- OpenCV all the functions and classes in a namespace inside cv, may be used
- using namespace cv;
-
#define HAVE_OPENCV_CALIB3D #define HAVE_OPENCV_CONTRIB #define HAVE_OPENCV_CORE #define HAVE_OPENCV_FEATURES2D #define HAVE_OPENCV_FLANN #define HAVE_OPENCV_GPU #define HAVE_OPENCV_HIGHGUI #define HAVE_OPENCV_IMGPROC #define HAVE_OPENCV_LEGACY #define HAVE_OPENCV_ML #define HAVE_OPENCV_NONFREE #define HAVE_OPENCV_OBJDETECT #define HAVE_OPENCV_OCL #define HAVE_OPENCV_PHOTO #define HAVE_OPENCV_STITCHING #define HAVE_OPENCV_SUPERRES #define HAVE_OPENCV_TS #define HAVE_OPENCV_VIDEO #define HAVE_OPENCV_VIDEOSTAB
1.opencv_core module
#include "opencv2/core/core_c.h"
#include "opencv2/core/core.hpp"
Comprising a core function (function of the underlying data structures and algorithms)
2.opencv_highgui module
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/highgui/highgui.hpp"
Image and video read function contains, and operating a graphical user interface function
3.opencv_imgproc module
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
Image processing functions comprising
4.opencv_photo module
#include "opencv2/photo/photo.hpp"
Containing the image restoration and image de-noising function
5.opencv_video module
#include "opencv2/video/video.hpp"
Comprising a video analysis (including motion estimation / foreground extraction and feature tracking function)
6.opencv_features2d module
#include "opencv/features2d/features2d.hpp"
It comprises interest point detection promoter / descriptor and points of interest matching the frame
7.opencv_calib3d module
#include "opencv2/calib3d/calib3d.hpp"
Comprising a camera calibration / binocular and stereoscopic geometric estimation function
8.opencv_objdetect module
#include "opencv2/objdetect/objdetect.hpp"
Comprising an object detection function (face / pedestrian detection)
9. Other Tools module
(1) opencv_ml module
#include "opencv2/ml/ml.hpp"
It includes machine learning
(2) opencv_flann module
#include "opencv2/flann/miniflann.hpp"
It includes computational geometry
(3) opencv_contrib module
#include "opencv2/contrib/contrib.hpp"
It contains other third-party code
II. Image common method
图像可以分为四种基本类型：二值图像、灰度图像、索引图像、RGB图像
线性代数 矩阵分析
图像处理常用的方法：
1.图像变换
2.图像编码与压缩
3.图像增强与复原
4.图像分割
5.图像描述
6.图像分类（识别）
7.图像恢复
8.图像匹配分析
一、256色转灰度图
二、Walsh变换
三、二值化变换
四、阈值变换
五、傅立叶变换
六、离散余弦变换
数字图像处理领域的二十四个典型算法及vc实现、第二章
七、高斯平滑
八、图像平移
九、图像缩放
十、图像旋转
Histogram equalization common edge extraction image sharpening filter binarization
III. Digital image processing content
1. point operations
Point operations mainly add / subtract / multiply / divide operation for the other pixels of the image. The image point operations can effectively change the distribution of the histogram of the image, and an image resolution can be provided a balanced image
2. geometric transformation
Including geometric transformation coordinate-converted images / moving / reduction / enlargement / selection, a plurality of image distortion correction and image registration
3. Image Enhancement
The main function of the image intensifier is important information for projecting the image, while the reduction or removal of unwanted information. Commonly used methods of gradation transformation enhancement / enhancement histogram / frequency enhancement, and color enhancement
The image restoration
The main purpose of image restoration is to remove interference and blurred, the restored image as it is., For example, to noise recovery processing methods commonly used linear and nonlinear restoring rehabilitation
The image is reconstructed
The reconstructed image originated in the development of CT technology, mainly using data collected to reconstruct the most widely used image, the main image reconstruction algorithms are the algebraic method / iterative method / inverse Fourier filtered back projection method and the use of projection
6. morphological image processing
Morphological image is an extension of mathematical morphology, the image can be achieved corrosion / expansion and thinning effects
The image segmentation
The main purpose is to divide the image segmentation of the region of interest out of the user, the main method of an edge Segmentation / thresholding method / area dividing method and texture segmentation methods
The image is encoded
The image coding mainly for image compression, develop a variety of coding standards
The image matching
Image matching means for identification between a plurality of images by a certain matching algorithm can be divided into a pixel basis matching and feature-based matching
Four .OpenCV process