OpenCV学习笔记四：ImgProc模块
一，简介
这个模块包含一系列的常用图像处理算法。
二，分析
此模块包含的文件如下图：
其导出算法包括如下：
/*********************** Background statistics accumulation *****************************/ /* Adds image to accumulator */
CVAPI(void) cvAcc( const CvArr* image, CvArr* sum,
const CvArr* mask CV_DEFAULT(NULL) ); /* Adds squared image to accumulator */
CVAPI(void) cvSquareAcc( const CvArr* image, CvArr* sqsum,
const CvArr* mask CV_DEFAULT(NULL) ); /* Adds a product of two images to accumulator */
CVAPI(void) cvMultiplyAcc( const CvArr* image1, const CvArr* image2, CvArr* acc,
const CvArr* mask CV_DEFAULT(NULL) ); /* Adds image to accumulator with weights: acc = acc*(1-alpha) + image*alpha */
CVAPI(void) cvRunningAvg( const CvArr* image, CvArr* acc, double alpha,
const CvArr* mask CV_DEFAULT(NULL) ); /****************************************************************************************\
* Image Processing *
\****************************************************************************************/ /* Copies source 2D array inside of the larger destination array and
makes a border of the specified type (IPL_BORDER_*) around the copied area. */
CVAPI(void) cvCopyMakeBorder( const CvArr* src, CvArr* dst, CvPoint offset,
int bordertype, CvScalar value CV_DEFAULT(cvScalarAll(0))); /* Smoothes array (removes noise) */
CVAPI(void) cvSmooth( const CvArr* src, CvArr* dst,
int smoothtype CV_DEFAULT(CV_GAUSSIAN),
int size1 CV_DEFAULT(3),
int size2 CV_DEFAULT(0),
double sigma1 CV_DEFAULT(0),
double sigma2 CV_DEFAULT(0)); /* Convolves the image with the kernel */
CVAPI(void) cvFilter2D( const CvArr* src, CvArr* dst, const CvMat* kernel,
CvPoint anchor CV_DEFAULT(cvPoint(-1,-1))); /* Finds integral image: SUM(X,Y) = sum(x<X,y<Y)I(x,y) */
CVAPI(void) cvIntegral( const CvArr* image, CvArr* sum,
CvArr* sqsum CV_DEFAULT(NULL),
CvArr* tilted_sum CV_DEFAULT(NULL)); /*
Smoothes the input image with gaussian kernel and then down-samples it.
dst_width = floor(src_width/2)[+1],
dst_height = floor(src_height/2)[+1]
*/
CVAPI(void) cvPyrDown( const CvArr* src, CvArr* dst,
int filter CV_DEFAULT(CV_GAUSSIAN_5x5) ); /*
Up-samples image and smoothes the result with gaussian kernel.
dst_width = src_width*2,
dst_height = src_height*2
*/
CVAPI(void) cvPyrUp( const CvArr* src, CvArr* dst,
int filter CV_DEFAULT(CV_GAUSSIAN_5x5) ); /* Builds pyramid for an image */
CVAPI(CvMat**) cvCreatePyramid( const CvArr* img, int extra_layers, double rate,
const CvSize* layer_sizes CV_DEFAULT(0),
CvArr* bufarr CV_DEFAULT(0),
int calc CV_DEFAULT(1),
int filter CV_DEFAULT(CV_GAUSSIAN_5x5) ); /* Releases pyramid */
CVAPI(void) cvReleasePyramid( CvMat*** pyramid, int extra_layers ); /* Filters image using meanshift algorithm */
CVAPI(void) cvPyrMeanShiftFiltering( const CvArr* src, CvArr* dst,
double sp, double sr, int max_level CV_DEFAULT(1),
CvTermCriteria termcrit CV_DEFAULT(cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,5,1))); /* Segments image using seed "markers" */
CVAPI(void) cvWatershed( const CvArr* image, CvArr* markers ); /* Calculates an image derivative using generalized Sobel
(aperture_size = 1,3,5,7) or Scharr (aperture_size = -1) operator.
Scharr can be used only for the first dx or dy derivative */
CVAPI(void) cvSobel( const CvArr* src, CvArr* dst,
int xorder, int yorder,
int aperture_size CV_DEFAULT(3)); /* Calculates the image Laplacian: (d2/dx + d2/dy)I */
CVAPI(void) cvLaplace( const CvArr* src, CvArr* dst,
int aperture_size CV_DEFAULT(3) ); /* Converts input array pixels from one color space to another */
CVAPI(void) cvCvtColor( const CvArr* src, CvArr* dst, int code ); /* Resizes image (input array is resized to fit the destination array) */
CVAPI(void) cvResize( const CvArr* src, CvArr* dst,
int interpolation CV_DEFAULT( CV_INTER_LINEAR )); /* Warps image with affine transform */
CVAPI(void) cvWarpAffine( const CvArr* src, CvArr* dst, const CvMat* map_matrix,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS),
CvScalar fillval CV_DEFAULT(cvScalarAll(0)) ); /* Computes affine transform matrix for mapping src[i] to dst[i] (i=0,1,2) */
CVAPI(CvMat*) cvGetAffineTransform( const CvPoint2D32f * src,
const CvPoint2D32f * dst,
CvMat * map_matrix ); /* Computes rotation_matrix matrix */
CVAPI(CvMat*) cv2DRotationMatrix( CvPoint2D32f center, double angle,
double scale, CvMat* map_matrix ); /* Warps image with perspective (projective) transform */
CVAPI(void) cvWarpPerspective( const CvArr* src, CvArr* dst, const CvMat* map_matrix,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS),
CvScalar fillval CV_DEFAULT(cvScalarAll(0)) ); /* Computes perspective transform matrix for mapping src[i] to dst[i] (i=0,1,2,3) */
CVAPI(CvMat*) cvGetPerspectiveTransform( const CvPoint2D32f* src,
const CvPoint2D32f* dst,
CvMat* map_matrix ); /* Performs generic geometric transformation using the specified coordinate maps */
CVAPI(void) cvRemap( const CvArr* src, CvArr* dst,
const CvArr* mapx, const CvArr* mapy,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS),
CvScalar fillval CV_DEFAULT(cvScalarAll(0)) ); /* Converts mapx & mapy from floating-point to integer formats for cvRemap */
CVAPI(void) cvConvertMaps( const CvArr* mapx, const CvArr* mapy,
CvArr* mapxy, CvArr* mapalpha ); /* Performs forward or inverse log-polar image transform */
CVAPI(void) cvLogPolar( const CvArr* src, CvArr* dst,
CvPoint2D32f center, double M,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS)); /* Performs forward or inverse linear-polar image transform */
CVAPI(void) cvLinearPolar( const CvArr* src, CvArr* dst,
CvPoint2D32f center, double maxRadius,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS)); /* Transforms the input image to compensate lens distortion */
CVAPI(void) cvUndistort2( const CvArr* src, CvArr* dst,
const CvMat* camera_matrix,
const CvMat* distortion_coeffs,
const CvMat* new_camera_matrix CV_DEFAULT(0) ); /* Computes transformation map from intrinsic camera parameters
that can used by cvRemap */
CVAPI(void) cvInitUndistortMap( const CvMat* camera_matrix,
const CvMat* distortion_coeffs,
CvArr* mapx, CvArr* mapy ); /* Computes undistortion+rectification map for a head of stereo camera */
CVAPI(void) cvInitUndistortRectifyMap( const CvMat* camera_matrix,
const CvMat* dist_coeffs,
const CvMat *R, const CvMat* new_camera_matrix,
CvArr* mapx, CvArr* mapy ); /* Computes the original (undistorted) feature coordinates
from the observed (distorted) coordinates */
CVAPI(void) cvUndistortPoints( const CvMat* src, CvMat* dst,
const CvMat* camera_matrix,
const CvMat* dist_coeffs,
const CvMat* R CV_DEFAULT(0),
const CvMat* P CV_DEFAULT(0)); /* creates structuring element used for morphological operations */
CVAPI(IplConvKernel*) cvCreateStructuringElementEx(
int cols, int rows, int anchor_x, int anchor_y,
int shape, int* values CV_DEFAULT(NULL) ); /* releases structuring element */
CVAPI(void) cvReleaseStructuringElement( IplConvKernel** element ); /* erodes input image (applies minimum filter) one or more times.
If element pointer is NULL, 3x3 rectangular element is used */
CVAPI(void) cvErode( const CvArr* src, CvArr* dst,
IplConvKernel* element CV_DEFAULT(NULL),
int iterations CV_DEFAULT(1) ); /* dilates input image (applies maximum filter) one or more times.
If element pointer is NULL, 3x3 rectangular element is used */
CVAPI(void) cvDilate( const CvArr* src, CvArr* dst,
IplConvKernel* element CV_DEFAULT(NULL),
int iterations CV_DEFAULT(1) ); /* Performs complex morphological transformation */
CVAPI(void) cvMorphologyEx( const CvArr* src, CvArr* dst,
CvArr* temp, IplConvKernel* element,
int operation, int iterations CV_DEFAULT(1) ); /* Calculates all spatial and central moments up to the 3rd order */
CVAPI(void) cvMoments( const CvArr* arr, CvMoments* moments, int binary CV_DEFAULT(0)); /* Retrieve particular spatial, central or normalized central moments */
CVAPI(double) cvGetSpatialMoment( CvMoments* moments, int x_order, int y_order );
CVAPI(double) cvGetCentralMoment( CvMoments* moments, int x_order, int y_order );
CVAPI(double) cvGetNormalizedCentralMoment( CvMoments* moments,
int x_order, int y_order ); /* Calculates 7 Hu's invariants from precalculated spatial and central moments */
CVAPI(void) cvGetHuMoments( CvMoments* moments, CvHuMoments* hu_moments ); /*********************************** data sampling **************************************/ /* Fetches pixels that belong to the specified line segment and stores them to the buffer.
Returns the number of retrieved points. */
CVAPI(int) cvSampleLine( const CvArr* image, CvPoint pt1, CvPoint pt2, void* buffer,
int connectivity CV_DEFAULT(8)); /* Retrieves the rectangular image region with specified center from the input array.
dst(x,y) <- src(x + center.x - dst_width/2, y + center.y - dst_height/2).
Values of pixels with fractional coordinates are retrieved using bilinear interpolation*/
CVAPI(void) cvGetRectSubPix( const CvArr* src, CvArr* dst, CvPoint2D32f center ); /* Retrieves quadrangle from the input array.
matrixarr = ( a11 a12 | b1 ) dst(x,y) <- src(A[x y]' + b)
( a21 a22 | b2 ) (bilinear interpolation is used to retrieve pixels
with fractional coordinates)
*/
CVAPI(void) cvGetQuadrangleSubPix( const CvArr* src, CvArr* dst,
const CvMat* map_matrix ); /* Measures similarity between template and overlapped windows in the source image
and fills the resultant image with the measurements */
CVAPI(void) cvMatchTemplate( const CvArr* image, const CvArr* templ,
CvArr* result, int method ); /* Computes earth mover distance between
two weighted point sets (called signatures) */
CVAPI(float) cvCalcEMD2( const CvArr* signature1,
const CvArr* signature2,
int distance_type,
CvDistanceFunction distance_func CV_DEFAULT(NULL),
const CvArr* cost_matrix CV_DEFAULT(NULL),
CvArr* flow CV_DEFAULT(NULL),
float* lower_bound CV_DEFAULT(NULL),
void* userdata CV_DEFAULT(NULL)); /****************************************************************************************\
* Contours retrieving *
\****************************************************************************************/ /* Retrieves outer and optionally inner boundaries of white (non-zero) connected
components in the black (zero) background */
CVAPI(int) cvFindContours( CvArr* image, CvMemStorage* storage, CvSeq** first_contour,
int header_size CV_DEFAULT(sizeof(CvContour)),
int mode CV_DEFAULT(CV_RETR_LIST),
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
CvPoint offset CV_DEFAULT(cvPoint(0,0))); /* Initalizes contour retrieving process.
Calls cvStartFindContours.
Calls cvFindNextContour until null pointer is returned
or some other condition becomes true.
Calls cvEndFindContours at the end. */
CVAPI(CvContourScanner) cvStartFindContours( CvArr* image, CvMemStorage* storage,
int header_size CV_DEFAULT(sizeof(CvContour)),
int mode CV_DEFAULT(CV_RETR_LIST),
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
CvPoint offset CV_DEFAULT(cvPoint(0,0))); /* Retrieves next contour */
CVAPI(CvSeq*) cvFindNextContour( CvContourScanner scanner ); /* Substitutes the last retrieved contour with the new one
(if the substitutor is null, the last retrieved contour is removed from the tree) */
CVAPI(void) cvSubstituteContour( CvContourScanner scanner, CvSeq* new_contour ); /* Releases contour scanner and returns pointer to the first outer contour */
CVAPI(CvSeq*) cvEndFindContours( CvContourScanner* scanner ); /* Approximates a single Freeman chain or a tree of chains to polygonal curves */
CVAPI(CvSeq*) cvApproxChains( CvSeq* src_seq, CvMemStorage* storage,
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
double parameter CV_DEFAULT(0),
int minimal_perimeter CV_DEFAULT(0),
int recursive CV_DEFAULT(0)); /* Initalizes Freeman chain reader.
The reader is used to iteratively get coordinates of all the chain points.
If the Freeman codes should be read as is, a simple sequence reader should be used */
CVAPI(void) cvStartReadChainPoints( CvChain* chain, CvChainPtReader* reader ); /* Retrieves the next chain point */
CVAPI(CvPoint) cvReadChainPoint( CvChainPtReader* reader ); /****************************************************************************************\
* Contour Processing and Shape Analysis *
\****************************************************************************************/ /* Approximates a single polygonal curve (contour) or
a tree of polygonal curves (contours) */
CVAPI(CvSeq*) cvApproxPoly( const void* src_seq,
int header_size, CvMemStorage* storage,
int method, double eps,
int recursive CV_DEFAULT(0)); /* Calculates perimeter of a contour or length of a part of contour */
CVAPI(double) cvArcLength( const void* curve,
CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ),
int is_closed CV_DEFAULT(-1)); CV_INLINE double cvContourPerimeter( const void* contour )
{
return cvArcLength( contour, CV_WHOLE_SEQ, 1 );
} /* Calculates contour boundning rectangle (update=1) or
just retrieves pre-calculated rectangle (update=0) */
CVAPI(CvRect) cvBoundingRect( CvArr* points, int update CV_DEFAULT(0) ); /* Calculates area of a contour or contour segment */
CVAPI(double) cvContourArea( const CvArr* contour,
CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ),
int oriented CV_DEFAULT(0)); /* Finds minimum area rotated rectangle bounding a set of points */
CVAPI(CvBox2D) cvMinAreaRect2( const CvArr* points,
CvMemStorage* storage CV_DEFAULT(NULL)); /* Finds minimum enclosing circle for a set of points */
CVAPI(int) cvMinEnclosingCircle( const CvArr* points,
CvPoint2D32f* center, float* radius ); /* Compares two contours by matching their moments */
CVAPI(double) cvMatchShapes( const void* object1, const void* object2,
int method, double parameter CV_DEFAULT(0)); /* Calculates exact convex hull of 2d point set */
CVAPI(CvSeq*) cvConvexHull2( const CvArr* input,
void* hull_storage CV_DEFAULT(NULL),
int orientation CV_DEFAULT(CV_CLOCKWISE),
int return_points CV_DEFAULT(0)); /* Checks whether the contour is convex or not (returns 1 if convex, 0 if not) */
CVAPI(int) cvCheckContourConvexity( const CvArr* contour ); /* Finds convexity defects for the contour */
CVAPI(CvSeq*) cvConvexityDefects( const CvArr* contour, const CvArr* convexhull,
CvMemStorage* storage CV_DEFAULT(NULL)); /* Fits ellipse into a set of 2d points */
CVAPI(CvBox2D) cvFitEllipse2( const CvArr* points ); /* Finds minimum rectangle containing two given rectangles */
CVAPI(CvRect) cvMaxRect( const CvRect* rect1, const CvRect* rect2 ); /* Finds coordinates of the box vertices */
CVAPI(void) cvBoxPoints( CvBox2D box, CvPoint2D32f pt[4] ); /* Initializes sequence header for a matrix (column or row vector) of points -
a wrapper for cvMakeSeqHeaderForArray (it does not initialize bounding rectangle!!!) */
CVAPI(CvSeq*) cvPointSeqFromMat( int seq_kind, const CvArr* mat,
CvContour* contour_header,
CvSeqBlock* block ); /* Checks whether the point is inside polygon, outside, on an edge (at a vertex).
Returns positive, negative or zero value, correspondingly.
Optionally, measures a signed distance between
the point and the nearest polygon edge (measure_dist=1) */
CVAPI(double) cvPointPolygonTest( const CvArr* contour,
CvPoint2D32f pt, int measure_dist ); /****************************************************************************************\
* Histogram functions *
\****************************************************************************************/ /* Creates new histogram */
CVAPI(CvHistogram*) cvCreateHist( int dims, int* sizes, int type,
float** ranges CV_DEFAULT(NULL),
int uniform CV_DEFAULT(1)); /* Assignes histogram bin ranges */
CVAPI(void) cvSetHistBinRanges( CvHistogram* hist, float** ranges,
int uniform CV_DEFAULT(1)); /* Creates histogram header for array */
CVAPI(CvHistogram*) cvMakeHistHeaderForArray(
int dims, int* sizes, CvHistogram* hist,
float* data, float** ranges CV_DEFAULT(NULL),
int uniform CV_DEFAULT(1)); /* Releases histogram */
CVAPI(void) cvReleaseHist( CvHistogram** hist ); /* Clears all the histogram bins */
CVAPI(void) cvClearHist( CvHistogram* hist ); /* Finds indices and values of minimum and maximum histogram bins */
CVAPI(void) cvGetMinMaxHistValue( const CvHistogram* hist,
float* min_value, float* max_value,
int* min_idx CV_DEFAULT(NULL),
int* max_idx CV_DEFAULT(NULL)); /* Normalizes histogram by dividing all bins by sum of the bins, multiplied by <factor>.
After that sum of histogram bins is equal to <factor> */
CVAPI(void) cvNormalizeHist( CvHistogram* hist, double factor ); /* Clear all histogram bins that are below the threshold */
CVAPI(void) cvThreshHist( CvHistogram* hist, double threshold ); /* Compares two histogram */
CVAPI(double) cvCompareHist( const CvHistogram* hist1,
const CvHistogram* hist2,
int method); /* Copies one histogram to another. Destination histogram is created if
the destination pointer is NULL */
CVAPI(void) cvCopyHist( const CvHistogram* src, CvHistogram** dst ); /* Calculates bayesian probabilistic histograms
(each or src and dst is an array of <number> histograms */
CVAPI(void) cvCalcBayesianProb( CvHistogram** src, int number,
CvHistogram** dst); /* Calculates array histogram */
CVAPI(void) cvCalcArrHist( CvArr** arr, CvHistogram* hist,
int accumulate CV_DEFAULT(0),
const CvArr* mask CV_DEFAULT(NULL) ); CV_INLINE void cvCalcHist( IplImage** image, CvHistogram* hist,
int accumulate CV_DEFAULT(0),
const CvArr* mask CV_DEFAULT(NULL) )
{
cvCalcArrHist( (CvArr**)image, hist, accumulate, mask );
} /* Calculates back project */
CVAPI(void) cvCalcArrBackProject( CvArr** image, CvArr* dst,
const CvHistogram* hist );
#define cvCalcBackProject(image, dst, hist) cvCalcArrBackProject((CvArr**)image, dst, hist) /* Does some sort of template matching but compares histograms of
template and each window location */
CVAPI(void) cvCalcArrBackProjectPatch( CvArr** image, CvArr* dst, CvSize range,
CvHistogram* hist, int method,
double factor );
#define cvCalcBackProjectPatch( image, dst, range, hist, method, factor ) \
cvCalcArrBackProjectPatch( (CvArr**)image, dst, range, hist, method, factor ) /* calculates probabilistic density (divides one histogram by another) */
CVAPI(void) cvCalcProbDensity( const CvHistogram* hist1, const CvHistogram* hist2,
CvHistogram* dst_hist, double scale CV_DEFAULT(255) ); /* equalizes histogram of 8-bit single-channel image */
CVAPI(void) cvEqualizeHist( const CvArr* src, CvArr* dst ); /* Applies distance transform to binary image */
CVAPI(void) cvDistTransform( const CvArr* src, CvArr* dst,
int distance_type CV_DEFAULT(CV_DIST_L2),
int mask_size CV_DEFAULT(3),
const float* mask CV_DEFAULT(NULL),
CvArr* labels CV_DEFAULT(NULL),
int labelType CV_DEFAULT(CV_DIST_LABEL_CCOMP)); /* Applies fixed-level threshold to grayscale image.
This is a basic operation applied before retrieving contours */
CVAPI(double) cvThreshold( const CvArr* src, CvArr* dst,
double threshold, double max_value,
int threshold_type ); /* Applies adaptive threshold to grayscale image.
The two parameters for methods CV_ADAPTIVE_THRESH_MEAN_C and
CV_ADAPTIVE_THRESH_GAUSSIAN_C are:
neighborhood size (3, 5, 7 etc.),
and a constant subtracted from mean (...,-3,-2,-1,0,1,2,3,...) */
CVAPI(void) cvAdaptiveThreshold( const CvArr* src, CvArr* dst, double max_value,
int adaptive_method CV_DEFAULT(CV_ADAPTIVE_THRESH_MEAN_C),
int threshold_type CV_DEFAULT(CV_THRESH_BINARY),
int block_size CV_DEFAULT(3),
double param1 CV_DEFAULT(5)); /* Fills the connected component until the color difference gets large enough */
CVAPI(void) cvFloodFill( CvArr* image, CvPoint seed_point,
CvScalar new_val, CvScalar lo_diff CV_DEFAULT(cvScalarAll(0)),
CvScalar up_diff CV_DEFAULT(cvScalarAll(0)),
CvConnectedComp* comp CV_DEFAULT(NULL),
int flags CV_DEFAULT(4),
CvArr* mask CV_DEFAULT(NULL)); /****************************************************************************************\
* Feature detection *
\****************************************************************************************/ /* Runs canny edge detector */
CVAPI(void) cvCanny( const CvArr* image, CvArr* edges, double threshold1,
double threshold2, int aperture_size CV_DEFAULT(3) ); /* Calculates constraint image for corner detection
Dx^2 * Dyy + Dxx * Dy^2 - 2 * Dx * Dy * Dxy.
Applying threshold to the result gives coordinates of corners */
CVAPI(void) cvPreCornerDetect( const CvArr* image, CvArr* corners,
int aperture_size CV_DEFAULT(3) ); /* Calculates eigen values and vectors of 2x2
gradient covariation matrix at every image pixel */
CVAPI(void) cvCornerEigenValsAndVecs( const CvArr* image, CvArr* eigenvv,
int block_size, int aperture_size CV_DEFAULT(3) ); /* Calculates minimal eigenvalue for 2x2 gradient covariation matrix at
every image pixel */
CVAPI(void) cvCornerMinEigenVal( const CvArr* image, CvArr* eigenval,
int block_size, int aperture_size CV_DEFAULT(3) ); /* Harris corner detector:
Calculates det(M) - k*(trace(M)^2), where M is 2x2 gradient covariation matrix for each pixel */
CVAPI(void) cvCornerHarris( const CvArr* image, CvArr* harris_responce,
int block_size, int aperture_size CV_DEFAULT(3),
double k CV_DEFAULT(0.04) ); /* Adjust corner position using some sort of gradient search */
CVAPI(void) cvFindCornerSubPix( const CvArr* image, CvPoint2D32f* corners,
int count, CvSize win, CvSize zero_zone,
CvTermCriteria criteria ); /* Finds a sparse set of points within the selected region
that seem to be easy to track */
CVAPI(void) cvGoodFeaturesToTrack( const CvArr* image, CvArr* eig_image,
CvArr* temp_image, CvPoint2D32f* corners,
int* corner_count, double quality_level,
double min_distance,
const CvArr* mask CV_DEFAULT(NULL),
int block_size CV_DEFAULT(3),
int use_harris CV_DEFAULT(0),
double k CV_DEFAULT(0.04) ); /* Finds lines on binary image using one of several methods.
line_storage is either memory storage or 1 x <max number of lines> CvMat, its
number of columns is changed by the function.
method is one of CV_HOUGH_*;
rho, theta and threshold are used for each of those methods;
param1 ~ line length, param2 ~ line gap - for probabilistic,
param1 ~ srn, param2 ~ stn - for multi-scale */
CVAPI(CvSeq*) cvHoughLines2( CvArr* image, void* line_storage, int method,
double rho, double theta, int threshold,
double param1 CV_DEFAULT(0), double param2 CV_DEFAULT(0)); /* Finds circles in the image */
CVAPI(CvSeq*) cvHoughCircles( CvArr* image, void* circle_storage,
int method, double dp, double min_dist,
double param1 CV_DEFAULT(100),
double param2 CV_DEFAULT(100),
int min_radius CV_DEFAULT(0),
int max_radius CV_DEFAULT(0)); /* Fits a line into set of 2d or 3d points in a robust way (M-estimator technique) */
CVAPI(void) cvFitLine( const CvArr* points, int dist_type, double param,
double reps, double aeps, float* line );
------------------------------------------------------------------------------------------------------
头文件：
types_c.h ， 定义了连通区域结构CvConnectedComp，平滑算法ID，颜色空间转换ID，像素插值算法ID，形状类型ID（RECT,CROSS等），形态学算法ID，中心矩/空间矩结构CvMoments，CvHuMoments，模板匹配类型ID，轮廓，形状匹配算法ID，直方图比较算法ID，二值化算法ID，泛洪算法类型，边缘检测，hough变换算法ID；
imgporc_c.h ，C/C++兼容头文件，其定义见上述函数列表；
imgproc.hpp，C++ only头文件，其定义参考imgproc_c.h
------------------------------------------------------------------------------------------------------
实现文件：
实现文件内容与文件名匹配，诸多算法均在其中一一有实现，目前不做具体分析。
------------------------------------------------------------------------------------------------------
三，总结
opencv包含常见的颜色空间转换，图像缩放，形态学操作等基本图像处理算法；也包含二值化，边缘检测，模板匹配，轮廓检测，直方图，泛洪，hough变换等高级主题。可在需要时研究相关实现，或者向其中添加所需算法。作为一个图像处理包，经过优化测试之后可应用于实际工业环境中。
OpenCV学习笔记四：ImgProc模块的更多相关文章
- OpenCV学习笔记：opencv_highgui模块
一,简介 本模块为跨平台的gui/IO组件,支持平台包括windows,linux,mac,IOS,android,可支持图像/视频/摄像头的读取显示以及转码. 二,分析 本模块为跨平台的gui/IO ...
- 【opencv学习笔记四】opencv3.4.0图形用户接口highgui函数解析
在笔记二中我们已经知道了,在highgui文件夹下的正是opencv图形用户接口功能结构,我们这篇博客所说的便是D:\Program Files\opencv340\opencv\build\incl ...
- OpenCV学习笔记：opencv_core模块
一,简介: opencv最基础的库.包含exception,point,rect,size,slice,vector,matrix,image等数据结构,和相应的操作函数,以及一些基础算法. 二,分析 ...
- OpenCV学习笔记：opencv_ml模块
一,简介 该模块为opencv的机器学习(machine learning,ml)代码库,包含各种机器学习算法: 0, class CvStatModel ; class CvMLData; stru ...
- Node.js学习笔记(四) --- fs模块的使用
目录 . fs.stat 检测是文件还是目录 . fs.mkdir 创建目录 . fs.writeFile 创建写入文件 . fs.appendFile 追加文件 . fs.readFile 读取文件 ...
- opencv学习笔记(四)--图像平滑处理
图像平滑处理的几种常用方法: 均值滤波 归一化滤波 高斯模糊 中值滤波 平滑处理(模糊)的主要目的是去燥声: 不同的处理方式适合不同的噪声图像,其中高斯模糊最常用. 其实最重要的是对图像卷积的核的理解 ...
- opencv学习笔记（四）投影
opencv学习笔记(四)投影 任选了一张图片用于测试,图片如下所示: #include <cv.h> #include <highgui.h> using namespace ...
- opencv学习笔记（二）寻找轮廓
opencv学习笔记(二)寻找轮廓 opencv中使用findContours函数来查找轮廓,这个函数的原型为: void findContours(InputOutputArray image, O ...
- OpenCV学习笔记（27）KAZE 算法原理与源码分析（一）非线性扩散滤波
http://blog.csdn.net/chenyusiyuan/article/details/8710462 OpenCV学习笔记(27)KAZE 算法原理与源码分析(一)非线性扩散滤波 201 ...
随机推荐
- javascript快速入门18--样式
修改元素外观方式 修改元素外观主要有下面3种方法:修改ID,修改className,修改元素的style属性 修改ID?会造成多么混乱的结果可想而知! 修改className确实是非常好的方法,我们甚 ...
- windows + myeclipse 调试 linux + tomcat 的java web服务 配置方式
一.linux tomcat配置和启动 1.catalina.sh第一行加入 declare -x CATALINA_OPTS="-Xdebug -Xrunjdwp:transport=dt ...
- Json杂谈系列------（一）初始json
1. JSON 是什么 JSON,全称是 JavaScript Object Notation,即 JavaScript 对象标记法.这是一种轻量级(Light-Weight).基于文本的(Text- ...
- Linux学习笔记 （七）挂载命令
在Linux中,光盘,U盘,硬盘在使用之前必须进行挂载,挂载类似windows中的分配盘符. 一.查看挂载和自动挂载 1.mount:直接输入mount表示查看系统中所有的挂载点. 2.mount - ...
- Oracle 查询搜索字符串在哪些存储过程中包含
如下: select *from all_source where OWNER = 'LC0019999'and TEXT like '%insert into%d values(%'
- PHP-深入理解Opcode缓存
1.什么是opcode缓存? 当解释器完成对脚本代码的分析后,便将它们生成可以直接运行的中间代码,也称为操作码(Operate Code,opcode).Opcode cache的目地是避免重复编译, ...
- 使用CAsyncSocket总结
最近想起CAsyncSocket这个类,记得很早以前用过,现在却想不起来怎么用了,翻了翻以前的代码又看了看msdn感觉这个类做简单的异步socket太简单了,几行代码就可以搞定,在此先做个总结. 不管 ...
- LA 5009 (HDU 3714) Error Curves （三分）
Error Curves Time Limit:3000MS Memory Limit:0KB 64bit IO Format:%lld & %llu SubmitStatusPr ...
- SGU180:Inversions(树状数组)
There are N integers (1<=N<=65537) A1, A2,.. AN (0<=Ai<=10^9). You need to find amount o ...
- tcpdump抓包（转）
Linux 环境下,通常通过 tcpdump 来进行抓包和分析.它是几乎所有 Linux 发行版本预装的数据包抓取和分析工具. tcpdump 工具的获取和安装可以参阅相应操作系统的官方文档,本文不再 ...