#include "opencv2/core.hpp"
#include "./imgproc/segmentation.hpp"

imgproc.hpp 的包含依赖关系图

此图显示哪些文件直接或间接包含此文件

类
类	cv::CLAHE
	对比度受限自适应直方图均衡化的基类。更多…

类	cv::GeneralizedHough
	使用广义霍夫变换在灰度图像中查找任意模板更多…

类	cv::GeneralizedHoughBallard
	使用广义霍夫变换在灰度图像中查找任意模板更多…

类	cv::GeneralizedHoughGuil
	使用广义霍夫变换在灰度图像中查找任意模板更多…

类	cv::LineIterator
	用于迭代光栅线段上所有像素的类。更多…

类	cv::LineSegmentDetector
	线段检测器类。更多…

结构体	cv::Subdiv2D::QuadEdge

类	cv::Subdiv2D

结构体	cv::Subdiv2D::Vertex

命名空间
命名空间	cv

宏
#define	CV_RGB(r, g, b)

枚举
枚举	cv::AdaptiveThresholdTypes { cv::ADAPTIVE_THRESH_MEAN_C = 0 , cv::ADAPTIVE_THRESH_GAUSSIAN_C = 1 }

枚举	cv::ColorConversionCodes { cv::COLOR_BGR2BGRA = 0 , cv::COLOR_RGB2RGBA = COLOR_BGR2BGRA , cv::COLOR_BGRA2BGR = 1 , cv::COLOR_RGBA2RGB = COLOR_BGRA2BGR , cv::COLOR_BGR2RGBA = 2 , cv::COLOR_RGB2BGRA = COLOR_BGR2RGBA , cv::COLOR_RGBA2BGR = 3 , cv::COLOR_BGRA2RGB = COLOR_RGBA2BGR , cv::COLOR_BGR2RGB = 4 , cv::COLOR_RGB2BGR = COLOR_BGR2RGB , cv::COLOR_BGRA2RGBA = 5 , cv::COLOR_RGBA2BGRA = COLOR_BGRA2RGBA , cv::COLOR_BGR2GRAY = 6 , cv::COLOR_RGB2GRAY = 7 , cv::COLOR_GRAY2BGR = 8 , cv::COLOR_GRAY2RGB = COLOR_GRAY2BGR , cv::COLOR_GRAY2BGRA = 9 , cv::COLOR_GRAY2RGBA = COLOR_GRAY2BGRA , cv::COLOR_BGRA2GRAY = 10 , cv::COLOR_RGBA2GRAY = 11 , cv::COLOR_BGR2BGR565 = 12 , cv::COLOR_RGB2BGR565 = 13 , cv::COLOR_BGR5652BGR = 14 , cv::COLOR_BGR5652RGB = 15 , cv::COLOR_BGRA2BGR565 = 16 , cv::COLOR_RGBA2BGR565 = 17 , cv::COLOR_BGR5652BGRA = 18 , cv::COLOR_BGR5652RGBA = 19 , cv::COLOR_GRAY2BGR565 = 20 , cv::COLOR_BGR5652GRAY = 21 , cv::COLOR_BGR2BGR555 = 22 , cv::COLOR_RGB2BGR555 = 23 , cv::COLOR_BGR5552BGR = 24 , cv::COLOR_BGR5552RGB = 25 , cv::COLOR_BGRA2BGR555 = 26 , cv::COLOR_RGBA2BGR555 = 27 , cv::COLOR_BGR5552BGRA = 28 , cv::COLOR_BGR5552RGBA = 29 , cv::COLOR_GRAY2BGR555 = 30 , cv::COLOR_BGR5552GRAY = 31 , cv::COLOR_BGR2XYZ = 32 , cv::COLOR_RGB2XYZ = 33 , cv::COLOR_XYZ2BGR = 34 , cv::COLOR_XYZ2RGB = 35 , cv::COLOR_BGR2YCrCb = 36 , cv::COLOR_RGB2YCrCb = 37 , cv::COLOR_YCrCb2BGR = 38 , cv::COLOR_YCrCb2RGB = 39 , cv::COLOR_BGR2HSV = 40 , cv::COLOR_RGB2HSV = 41 , cv::COLOR_BGR2Lab = 44 , cv::COLOR_RGB2Lab = 45 , cv::COLOR_BGR2Luv = 50 , cv::COLOR_RGB2Luv = 51 , cv::COLOR_BGR2HLS = 52 , cv::COLOR_RGB2HLS = 53 , cv::COLOR_HSV2BGR = 54 , cv::COLOR_HSV2RGB = 55 , cv::COLOR_Lab2BGR = 56 , cv::COLOR_Lab2RGB = 57 , cv::COLOR_Luv2BGR = 58 , cv::COLOR_Luv2RGB = 59 , cv::COLOR_HLS2BGR = 60 , cv::COLOR_HLS2RGB = 61 , cv::COLOR_BGR2HSV_FULL = 66 , cv::COLOR_RGB2HSV_FULL = 67 , cv::COLOR_BGR2HLS_FULL = 68 , cv::COLOR_RGB2HLS_FULL = 69 , cv::COLOR_HSV2BGR_FULL = 70 , cv::COLOR_HSV2RGB_FULL = 71 , cv::COLOR_HLS2BGR_FULL = 72 , cv::COLOR_HLS2RGB_FULL = 73 , cv::COLOR_LBGR2Lab = 74 , cv::COLOR_LRGB2Lab = 75 , cv::COLOR_LBGR2Luv = 76 , cv::COLOR_LRGB2Luv = 77 , cv::COLOR_Lab2LBGR = 78 , cv::COLOR_Lab2LRGB = 79 , cv::COLOR_Luv2LBGR = 80 , cv::COLOR_Luv2LRGB = 81 , cv::COLOR_BGR2YUV = 82 , cv::COLOR_RGB2YUV = 83 , cv::COLOR_YUV2BGR = 84 , cv::COLOR_YUV2RGB = 85 , cv::COLOR_YUV2RGB_NV12 = 90 , cv::COLOR_YUV2BGR_NV12 = 91 , cv::COLOR_YUV2RGB_NV21 = 92 , cv::COLOR_YUV2BGR_NV21 = 93 , cv::COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21 , cv::COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21 , cv::COLOR_YUV2RGBA_NV12 = 94 , cv::COLOR_YUV2BGRA_NV12 = 95 , cv::COLOR_YUV2RGBA_NV21 = 96 , cv::COLOR_YUV2BGRA_NV21 = 97 , cv::COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21 , cv::COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21 , cv::COLOR_YUV2RGB_YV12 = 98 , cv::COLOR_YUV2BGR_YV12 = 99 , cv::COLOR_YUV2RGB_IYUV = 100 , cv::COLOR_YUV2BGR_IYUV = 101 , cv::COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV , cv::COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV , cv::COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12 , cv::COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12 , cv::COLOR_YUV2RGBA_YV12 = 102 , cv::COLOR_YUV2BGRA_YV12 = 103 , cv::COLOR_YUV2RGBA_IYUV = 104 , cv::COLOR_YUV2BGRA_IYUV = 105 , cv::COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV , cv::COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV , cv::COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12 , cv::COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12 , cv::COLOR_YUV2GRAY_420 = 106 , cv::COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420 cv::COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420 cv::COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420 cv::COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420 cv::COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420 cv::COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420 cv::COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420 cv::COLOR_YUV2RGB_UYVY = 107 , cv::COLOR_YUV2BGR_UYVY = 108 , cv::COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY cv::COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY cv::COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY cv::COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY cv::COLOR_YUV2RGBA_UYVY = 111 , cv::COLOR_YUV2BGRA_UYVY = 112 , cv::COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY cv::COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY cv::COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY cv::COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY cv::COLOR_YUV2RGB_YUY2 = 115 , cv::COLOR_YUV2BGR_YUY2 = 116 , cv::COLOR_YUV2RGB_YVYU = 117 , cv::COLOR_YUV2BGR_YVYU = 118 , cv::COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2 cv::COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2 cv::COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2 cv::COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2 cv::COLOR_YUV2RGBA_YUY2 = 119 , cv::COLOR_YUV2BGRA_YUY2 = 120 , cv::COLOR_YUV2RGBA_YVYU = 121 , cv::COLOR_YUV2BGRA_YVYU = 122 , cv::COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2 cv::COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2 cv::COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2 cv::COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2 cv::COLOR_YUV2GRAY_UYVY = 123 , cv::COLOR_YUV2GRAY_YUY2 = 124 , cv::COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY cv::COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY cv::COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2 cv::COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2 cv::COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2 cv::COLOR_RGBA2mRGBA = 125 , cv::COLOR_mRGBA2RGBA = 126 , cv::COLOR_RGB2YUV_I420 = 127 , cv::COLOR_BGR2YUV_I420 = 128 , cv::COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420 cv::COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420 cv::COLOR_RGBA2YUV_I420 = 129 , cv::COLOR_BGRA2YUV_I420 = 130 , cv::COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420 cv::COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420 cv::COLOR_RGB2YUV_YV12 = 131 , cv::COLOR_BGR2YUV_YV12 = 132 , cv::COLOR_RGBA2YUV_YV12 = 133 , cv::COLOR_BGRA2YUV_YV12 = 134 , cv::COLOR_BayerBG2BGR = 46 , cv::COLOR_BayerGB2BGR = 47 , cv::COLOR_BayerRG2BGR = 48 , cv::COLOR_BayerGR2BGR = 49 , cv::COLOR_BayerRGGB2BGR = COLOR_BayerBG2BGR cv::COLOR_BayerGRBG2BGR = COLOR_BayerGB2BGR cv::COLOR_BayerBGGR2BGR = COLOR_BayerRG2BGR cv::COLOR_BayerGBRG2BGR = COLOR_BayerGR2BGR cv::COLOR_BayerRGGB2RGB = COLOR_BayerBGGR2BGR cv::COLOR_BayerGRBG2RGB = COLOR_BayerGBRG2BGR cv::COLOR_BayerBGGR2RGB = COLOR_BayerRGGB2BGR cv::COLOR_BayerGBRG2RGB = COLOR_BayerGRBG2BGR cv::COLOR_BayerBG2RGB = COLOR_BayerRG2BGR cv::COLOR_BayerGB2RGB = COLOR_BayerGR2BGR cv::COLOR_BayerRG2RGB = COLOR_BayerBG2BGR cv::COLOR_BayerGR2RGB = COLOR_BayerGB2BGR cv::COLOR_BayerBG2GRAY = 86 , cv::COLOR_BayerGB2GRAY = 87 , cv::COLOR_BayerRG2GRAY = 88 , cv::COLOR_BayerGR2GRAY = 89 , cv::COLOR_BayerRGGB2GRAY = COLOR_BayerBG2GRAY cv::COLOR_BayerGRBG2GRAY = COLOR_BayerGB2GRAY cv::COLOR_BayerBGGR2GRAY = COLOR_BayerRG2GRAY cv::COLOR_BayerGBRG2GRAY = COLOR_BayerGR2GRAY cv::COLOR_BayerBG2BGR_VNG = 62 , cv::COLOR_BayerGB2BGR_VNG = 63 , cv::COLOR_BayerRG2BGR_VNG = 64 , cv::COLOR_BayerGR2BGR_VNG = 65 , cv::COLOR_BayerRGGB2BGR_VNG = COLOR_BayerBG2BGR_VNG cv::COLOR_BayerGRBG2BGR_VNG = COLOR_BayerGB2BGR_VNG cv::COLOR_BayerBGGR2BGR_VNG = COLOR_BayerRG2BGR_VNG cv::COLOR_BayerGBRG2BGR_VNG = COLOR_BayerGR2BGR_VNG cv::COLOR_BayerRGGB2RGB_VNG = COLOR_BayerBGGR2BGR_VNG cv::COLOR_BayerGRBG2RGB_VNG = COLOR_BayerGBRG2BGR_VNG cv::COLOR_BayerBGGR2RGB_VNG = COLOR_BayerRGGB2BGR_VNG cv::COLOR_BayerGBRG2RGB_VNG = COLOR_BayerGRBG2BGR_VNG cv::COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG cv::COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG cv::COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG cv::COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG cv::COLOR_BayerBG2BGR_EA = 135 , cv::COLOR_BayerGB2BGR_EA = 136 , cv::COLOR_BayerRG2BGR_EA = 137 , cv::COLOR_BayerGR2BGR_EA = 138 , cv::COLOR_BayerRGGB2BGR_EA = COLOR_BayerBG2BGR_EA cv::COLOR_BayerGRBG2BGR_EA = COLOR_BayerGB2BGR_EA cv::COLOR_BayerBGGR2BGR_EA = COLOR_BayerRG2BGR_EA cv::COLOR_BayerGBRG2BGR_EA = COLOR_BayerGR2BGR_EA cv::COLOR_BayerRGGB2RGB_EA = COLOR_BayerBGGR2BGR_EA cv::COLOR_BayerGRBG2RGB_EA = COLOR_BayerGBRG2BGR_EA cv::COLOR_BayerBGGR2RGB_EA = COLOR_BayerRGGB2BGR_EA cv::COLOR_BayerGBRG2RGB_EA = COLOR_BayerGRBG2BGR_EA cv::COLOR_BayerBG2RGB_EA = COLOR_BayerRG2BGR_EA cv::COLOR_BayerGB2RGB_EA = COLOR_BayerGR2BGR_EA cv::COLOR_BayerRG2RGB_EA = COLOR_BayerBG2BGR_EA cv::COLOR_BayerGR2RGB_EA = COLOR_BayerGB2BGR_EA cv::COLOR_BayerBG2BGRA = 139 , cv::COLOR_BayerGB2BGRA = 140 , cv::COLOR_BayerRG2BGRA = 141 , cv::COLOR_BayerGR2BGRA = 142 , cv::COLOR_BayerRGGB2BGRA = COLOR_BayerBG2BGRA cv::COLOR_BayerGRBG2BGRA = COLOR_BayerGB2BGRA cv::COLOR_BayerBGGR2BGRA = COLOR_BayerRG2BGRA cv::COLOR_BayerGBRG2BGRA = COLOR_BayerGR2BGRA cv::COLOR_BayerRGGB2RGBA = COLOR_BayerBGGR2BGRA cv::COLOR_BayerGRBG2RGBA = COLOR_BayerGBRG2BGRA cv::COLOR_BayerBGGR2RGBA = COLOR_BayerRGGB2BGRA cv::COLOR_BayerGBRG2RGBA = COLOR_BayerGRBG2BGRA cv::COLOR_BayerBG2RGBA = COLOR_BayerRG2BGRA cv::COLOR_BayerGB2RGBA = COLOR_BayerGR2BGRA cv::COLOR_BayerRG2RGBA = COLOR_BayerBG2BGRA cv::COLOR_BayerGR2RGBA = COLOR_BayerGB2BGRA cv::COLOR_RGB2YUV_UYVY = 143 , cv::COLOR_BGR2YUV_UYVY = 144 , cv::COLOR_RGB2YUV_Y422 = COLOR_RGB2YUV_UYVY cv::COLOR_BGR2YUV_Y422 = COLOR_BGR2YUV_UYVY cv::COLOR_RGB2YUV_UYNV = COLOR_RGB2YUV_UYVY cv::COLOR_BGR2YUV_UYNV = COLOR_BGR2YUV_UYVY cv::COLOR_RGBA2YUV_UYVY = 145 , cv::COLOR_BGRA2YUV_UYVY = 146 , cv::COLOR_RGBA2YUV_Y422 = COLOR_RGBA2YUV_UYVY cv::COLOR_BGRA2YUV_Y422 = COLOR_BGRA2YUV_UYVY cv::COLOR_RGBA2YUV_UYNV = COLOR_RGBA2YUV_UYVY cv::COLOR_BGRA2YUV_UYNV = COLOR_BGRA2YUV_UYVY cv::COLOR_RGB2YUV_YUY2 = 147 , cv::COLOR_BGR2YUV_YUY2 = 148 , cv::COLOR_RGB2YUV_YVYU = 149 , cv::COLOR_BGR2YUV_YVYU = 150 , cv::COLOR_RGB2YUV_YUYV = COLOR_RGB2YUV_YUY2 cv::COLOR_BGR2YUV_YUYV = COLOR_BGR2YUV_YUY2 cv::COLOR_RGB2YUV_YUNV = COLOR_RGB2YUV_YUY2 cv::COLOR_BGR2YUV_YUNV = COLOR_BGR2YUV_YUY2 cv::COLOR_RGBA2YUV_YUY2 = 151 , cv::COLOR_BGRA2YUV_YUY2 = 152 , cv::COLOR_RGBA2YUV_YVYU = 153 , cv::COLOR_BGRA2YUV_YVYU = 154 , cv::COLOR_RGBA2YUV_YUYV = COLOR_RGBA2YUV_YUY2 cv::COLOR_BGRA2YUV_YUYV = COLOR_BGRA2YUV_YUY2 cv::COLOR_RGBA2YUV_YUNV = COLOR_RGBA2YUV_YUY2 cv::COLOR_BGRA2YUV_YUNV = COLOR_BGRA2YUV_YUY2 cv::COLOR_COLORCVT_MAX = 155 }

枚举	cv::ColormapTypes { cv::COLORMAP_AUTUMN = 0 , cv::COLORMAP_BONE = 1 , cv::COLORMAP_JET = 2 , cv::COLORMAP_WINTER = 3 , cv::COLORMAP_RAINBOW = 4 , cv::COLORMAP_OCEAN = 5 , cv::COLORMAP_SUMMER = 6 , cv::COLORMAP_SPRING = 7 , cv::COLORMAP_COOL = 8 , cv::COLORMAP_HSV = 9 , cv::COLORMAP_PINK = 10 , cv::COLORMAP_HOT = 11 , cv::COLORMAP_PARULA = 12 , cv::COLORMAP_MAGMA = 13 , cv::COLORMAP_INFERNO = 14 , cv::COLORMAP_PLASMA = 15 , cv::COLORMAP_VIRIDIS = 16 , cv::COLORMAP_CIVIDIS = 17 , cv::COLORMAP_TWILIGHT = 18 , cv::COLORMAP_TWILIGHT_SHIFTED = 19 , cv::COLORMAP_TURBO = 20 , cv::COLORMAP_DEEPGREEN = 21 }
	GNU Octave/MATLAB 等效颜色映射。更多...

枚举	cv::ConnectedComponentsAlgorithmsTypes { cv::CCL_DEFAULT = -1 , cv::CCL_WU = 0 , cv::CCL_GRANA = 1 , cv::CCL_BOLELLI = 2 , cv::CCL_SAUF = 3 , cv::CCL_BBDT = 4 , cv::CCL_SPAGHETTI = 5 }
	连通分量算法更多...

枚举	cv::ConnectedComponentsTypes { cv::CC_STAT_LEFT = 0 , cv::CC_STAT_TOP = 1 , cv::CC_STAT_WIDTH = 2 , cv::CC_STAT_HEIGHT = 3 , cv::CC_STAT_AREA = 4 }
	连通组件统计信息更多...

枚举	cv::ContourApproximationModes { cv::CHAIN_APPROX_NONE = 1 , cv::CHAIN_APPROX_SIMPLE = 2 , cv::CHAIN_APPROX_TC89_L1 = 3 , cv::CHAIN_APPROX_TC89_KCOS = 4 }
	轮廓逼近算法更多...

枚举	cv::DistanceTransformLabelTypes { cv::DIST_LABEL_CCOMP = 0 , cv::DIST_LABEL_PIXEL = 1 }
	距离变换算法标志更多...

枚举	cv::DistanceTransformMasks { cv::DIST_MASK_3 = 3 , cv::DIST_MASK_5 = 5 , cv::DIST_MASK_PRECISE = 0 }
	距离变换的掩码大小。更多...

枚举	cv::DistanceTypes { cv::DIST_USER = -1 , cv::DIST_L1 = 1 , cv::DIST_L2 = 2 , cv::DIST_C = 3 , cv::DIST_L12 = 4 , cv::DIST_FAIR = 5 , cv::DIST_WELSCH = 6 , cv::DIST_HUBER = 7 }

枚举	cv::FloodFillFlags { cv::FLOODFILL_FIXED_RANGE = 1 << 16 , cv::FLOODFILL_MASK_ONLY = 1 << 17 }
	漫水填充算法标志更多...

枚举	cv::GrabCutClasses { cv::GC_BGD = 0 , cv::GC_FGD = 1 , cv::GC_PR_BGD = 2 , cv::GC_PR_FGD = 3 }
	GrabCut算法中像素的类别更多...

枚举	cv::GrabCutModes { cv::GC_INIT_WITH_RECT = 0 , cv::GC_INIT_WITH_MASK = 1 , cv::GC_EVAL = 2 , cv::GC_EVAL_FREEZE_MODEL = 3 }
	GrabCut算法标志。更多...

枚举	cv::HersheyFonts { cv::FONT_HERSHEY_SIMPLEX = 0 , cv::FONT_HERSHEY_PLAIN = 1 , cv::FONT_HERSHEY_DUPLEX = 2 , cv::FONT_HERSHEY_COMPLEX = 3 , cv::FONT_HERSHEY_TRIPLEX = 4 , cv::FONT_HERSHEY_COMPLEX_SMALL = 5 , cv::FONT_HERSHEY_SCRIPT_SIMPLEX = 6 , cv::FONT_HERSHEY_SCRIPT_COMPLEX = 7 , cv::FONT_ITALIC = 16 }

枚举	cv::HistCompMethods { cv::HISTCMP_CORREL = 0 , cv::HISTCMP_CHISQR = 1 , cv::HISTCMP_INTERSECT = 2 , cv::HISTCMP_BHATTACHARYYA = 3 , cv::HISTCMP_HELLINGER = HISTCMP_BHATTACHARYYA , cv::HISTCMP_CHISQR_ALT = 4 , cv::HISTCMP_KL_DIV = 5 }

枚举	cv::HoughModes { cv::HOUGH_STANDARD = 0 , cv::HOUGH_PROBABILISTIC = 1 , cv::HOUGH_MULTI_SCALE = 2 , cv::HOUGH_GRADIENT = 3 , cv::HOUGH_GRADIENT_ALT = 4 }
	霍夫变换的变体。更多...

枚举	cv::InterpolationFlags { cv::INTER_NEAREST = 0 , cv::INTER_LINEAR = 1 , cv::INTER_CUBIC = 2 , cv::INTER_AREA = 3 , cv::INTER_LANCZOS4 = 4 , cv::INTER_LINEAR_EXACT = 5 , cv::INTER_NEAREST_EXACT = 6 , cv::INTER_MAX = 7 , cv::WARP_FILL_OUTLIERS = 8 , cv::WARP_INVERSE_MAP = 16 , cv::WARP_RELATIVE_MAP = 32 }
	插值算法更多...

枚举	cv::InterpolationMasks { cv::INTER_BITS = 5 , cv::INTER_BITS2 = INTER_BITS * 2 , cv::INTER_TAB_SIZE = 1 << INTER_BITS , cv::INTER_TAB_SIZE2 = INTER_TAB_SIZE * INTER_TAB_SIZE }

枚举	cv::LineSegmentDetectorModes { cv::LSD_REFINE_NONE = 0 , cv::LSD_REFINE_STD = 1 , cv::LSD_REFINE_ADV = 2 }
	线段检测器的变体。更多...

枚举	cv::LineTypes { cv::FILLED = -1 , cv::LINE_4 = 4 , cv::LINE_8 = 8 , cv::LINE_AA = 16 }

枚举	cv::MarkerTypes { cv::MARKER_CROSS = 0 , cv::MARKER_TILTED_CROSS = 1 , cv::MARKER_STAR = 2 , cv::MARKER_DIAMOND = 3 , cv::MARKER_SQUARE = 4 , cv::MARKER_TRIANGLE_UP = 5 , cv::MARKER_TRIANGLE_DOWN = 6 }

枚举	cv::MorphShapes { cv::MORPH_RECT = 0 , cv::MORPH_CROSS = 1 , cv::MORPH_ELLIPSE = 2 }
	结构元素的形状更多...

枚举	cv::MorphTypes { cv::MORPH_ERODE = 0 , cv::MORPH_DILATE = 1 , cv::MORPH_OPEN = 2 , cv::MORPH_CLOSE = 3 , cv::MORPH_GRADIENT = 4 , cv::MORPH_TOPHAT = 5 , cv::MORPH_BLACKHAT = 6 , cv::MORPH_HITMISS = 7 }
	形态学运算的类型更多...

枚举	cv::RectanglesIntersectTypes { cv::INTERSECT_NONE = 0 , cv::INTERSECT_PARTIAL = 1 , cv::INTERSECT_FULL = 2 }
	矩形之间相交的类型更多...

枚举	cv::RetrievalModes { cv::RETR_EXTERNAL = 0 , cv::RETR_LIST = 1 , cv::RETR_CCOMP = 2 , cv::RETR_TREE = 3 , cv::RETR_FLOODFILL = 4 }
	轮廓检索算法的模式更多...

枚举	cv::ShapeMatchModes { cv::CONTOURS_MATCH_I1 =1 , cv::CONTOURS_MATCH_I2 =2 , cv::CONTOURS_MATCH_I3 =3 }
	形状匹配方法。更多...

枚举	cv::SpecialFilter { cv::FILTER_SCHARR = -1 }

枚举	cv::TemplateMatchModes { cv::TM_SQDIFF = 0 , cv::TM_SQDIFF_NORMED = 1 , cv::TM_CCORR = 2 , cv::TM_CCORR_NORMED = 3 , cv::TM_CCOEFF = 4 , cv::TM_CCOEFF_NORMED = 5 }
	模板匹配运算的类型更多...

枚举	cv::ThresholdTypes { cv::THRESH_BINARY = 0 , cv::THRESH_BINARY_INV = 1 , cv::THRESH_TRUNC = 2 , cv::THRESH_TOZERO = 3 , cv::THRESH_TOZERO_INV = 4 , cv::THRESH_MASK = 7 , cv::THRESH_OTSU = 8 , cv::THRESH_TRIANGLE = 16 }

枚举	cv::WarpPolarMode { cv::WARP_POLAR_LINEAR = 0 , cv::WARP_POLAR_LOG = 256 }
	指定极坐标映射模式。更多...

函数
void	cv::accumulate (InputArray src, InputOutputArray dst, InputArray mask=noArray())
	将图像添加到累加器图像。

void	cv::accumulateProduct (InputArray src1, InputArray src2, InputOutputArray dst, InputArray mask=noArray())
	将两个输入图像的逐元素乘积添加到累加器图像。

void	cv::accumulateSquare (InputArray src, InputOutputArray dst, InputArray mask=noArray())
	将源图像的平方添加到累加器图像。

void	cv::accumulateWeighted (InputArray src, InputOutputArray dst, double alpha, InputArray mask=noArray())
	更新运行平均值。

void	cv::adaptiveThreshold (InputArray src, OutputArray dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C)
	对数组应用自适应阈值。

void	cv::applyColorMap (InputArray src, OutputArray dst, InputArray userColor)
	对给定图像应用用户颜色映射。

void	cv::applyColorMap (InputArray src, OutputArray dst, int colormap)
	对给定图像应用 GNU Octave/MATLAB 等效颜色映射。

void	cv::approxPolyDP (InputArray curve, OutputArray approxCurve, double epsilon, bool closed)
	使用指定的精度逼近多边形曲线。

void	cv::approxPolyN (InputArray curve, OutputArray approxCurve, int nsides, float epsilon_percentage=-1.0, bool ensure_convex=true)
	使用指定的精度和边数逼近具有凸包的多边形。

double	cv::arcLength (InputArray curve, bool closed)
	计算轮廓周长或曲线长度。

void	cv::arrowedLine (InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int line_type=8, int shift=0, double tipLength=0.1)
	绘制从第一个点指向第二个点的箭头线段。

void	cv::bilateralFilter (InputArray src, OutputArray dst, int d, double sigmaColor, double sigmaSpace, int borderType=BORDER_DEFAULT)
	将双边滤波器应用于图像。

void	cv::blendLinear (InputArray src1, InputArray src2, InputArray weights1, InputArray weights2, OutputArray dst)

void	cv::blur (InputArray src, OutputArray dst, Size ksize, Point anchor=Point(-1,-1), int borderType=BORDER_DEFAULT)
	使用归一化盒式滤波器模糊图像。

Rect	cv::boundingRect (InputArray array)
	计算点集或灰度图像非零像素的右上方边界矩形。

void	cv::boxFilter (InputArray src, OutputArray dst, int ddepth, Size ksize, Point anchor=Point(-1,-1), bool normalize=true, int borderType=BORDER_DEFAULT)
	使用盒式滤波器模糊图像。

void	cv::boxPoints (RotatedRect box, OutputArray points)
	查找旋转矩形的四个顶点。用于绘制旋转矩形。

void	cv::buildPyramid (InputArray src, OutputArrayOfArrays dst, int maxlevel, int borderType=BORDER_DEFAULT)
	构建图像的高斯金字塔。

void	cv::calcBackProject (const Mat images, int nimages, const int channels, const SparseMat &hist, OutputArray backProject, const float **ranges, double scale=1, bool uniform=true)

void	cv::calcBackProject (const Mat images, int nimages, const int channels, InputArray hist, OutputArray backProject, const float **ranges, double scale=1, bool uniform=true)
	计算直方图的反向投影。

void	cv::calcBackProject (InputArrayOfArrays images, const std::vector< int > &channels, InputArray hist, OutputArray dst, const std::vector< float > &ranges, double scale)

void	cv::calcHist (const Mat images, int nimages, const int channels, InputArray mask, OutputArray hist, int dims, const int histSize, const float *ranges, bool uniform=true, bool accumulate=false)
	计算一组数组的直方图。

void	cv::calcHist (const Mat images, int nimages, const int channels, InputArray mask, SparseMat &hist, int dims, const int histSize, const float *ranges, bool uniform=true, bool accumulate=false)

void	cv::calcHist (InputArrayOfArrays images, const std::vector< int > &channels, InputArray mask, OutputArray hist, const std::vector< int > &histSize, const std::vector< float > &ranges, bool accumulate=false)

void	cv::Canny(InputArray dx, InputArray dy, OutputArray edges, double threshold1, double threshold2, bool L2gradient=false)

void	cv::Canny(InputArray image, OutputArray edges, double threshold1, double threshold2, int apertureSize=3, bool L2gradient=false)
	使用Canny算法[48]查找图像中的边缘。

void	cv::circle(InputOutputArray img, Point center, int radius, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
	绘制一个圆。

bool	cv::clipLine(Rect imgRect, Point &pt1, Point &pt2)

bool	cv::clipLine(Size imgSize, Point &pt1, Point &pt2)
	将线条裁剪到图像矩形范围内。

bool	cv::clipLine(Size2l imgSize, Point2l &pt1, Point2l &pt2)

double	cv::compareHist(const SparseMat &H1, const SparseMat &H2, int method)

double	cv::compareHist(InputArray H1, InputArray H2, int method)
	比较两个直方图。

int	cv::connectedComponents(InputArray image, OutputArray labels, int connectivity, int ltype, int ccltype)
	计算布尔图像的连通分量标记图像

int	cv::connectedComponents(InputArray image, OutputArray labels, int connectivity=8, int ltype=CV_32S)

int	cv::connectedComponentsWithStats(InputArray image, OutputArray labels, OutputArray stats, OutputArray centroids, int connectivity, int ltype, int ccltype)
	计算布尔图像的连通分量标记图像，并为每个标记生成统计输出。

int	cv::connectedComponentsWithStats(InputArray image, OutputArray labels, OutputArray stats, OutputArray centroids, int connectivity=8, int ltype=CV_32S)

double	cv::contourArea(InputArray contour, bool oriented=false)
	计算轮廓面积。

void	cv::convertMaps(InputArray map1, InputArray map2, OutputArray dstmap1, OutputArray dstmap2, int dstmap1type, bool nninterpolation=false)
	将图像变换映射从一种表示转换为另一种表示。

void	cv::convexHull(InputArray points, OutputArray hull, bool clockwise=false, bool returnPoints=true)
	查找点集的凸包。

void	cv::convexityDefects(InputArray contour, InputArray convexhull, OutputArray convexityDefects)
	查找轮廓的凸缺陷。

void	cv::cornerEigenValsAndVecs(InputArray src, OutputArray dst, int blockSize, int ksize, int borderType=BORDER_DEFAULT)
	计算图像块的特征值和特征向量，用于角点检测。

void	cv::cornerHarris(InputArray src, OutputArray dst, int blockSize, int ksize, double k, int borderType=BORDER_DEFAULT)
	Harris角点检测器。

void	cv::cornerMinEigenVal(InputArray src, OutputArray dst, int blockSize, int ksize=3, int borderType=BORDER_DEFAULT)
	计算用于角点检测的梯度矩阵的最小特征值。

void	cv::cornerSubPix(InputArray image, InputOutputArray corners, Size winSize, Size zeroZone, TermCriteria criteria)
	细化角点位置。

Ptr< CLAHE >	cv::createCLAHE(double clipLimit=40.0, Size tileGridSize=Size(8, 8))
	创建一个指向cv::CLAHE类的智能指针并对其进行初始化。

Ptr< GeneralizedHoughBallard >	cv::createGeneralizedHoughBallard ()
	创建一个指向cv::GeneralizedHoughBallard类的智能指针并对其进行初始化。

Ptr< GeneralizedHoughGuil >	cv::createGeneralizedHoughGuil ()
	创建一个指向cv::GeneralizedHoughGuil类的智能指针并对其进行初始化。

void	cv::createHanningWindow (OutputArray dst, Size winSize, int type)
	此函数计算二维汉宁窗系数。

Ptr< LineSegmentDetector >	cv::createLineSegmentDetector (int refine=LSD_REFINE_STD, double scale=0.8, double sigma_scale=0.6, double quant=2.0, double ang_th=22.5, double log_eps=0, double density_th=0.7, int n_bins=1024)
	创建一个指向LineSegmentDetector对象的智能指针并对其进行初始化。

void	cv::cvtColor (InputArray src, OutputArray dst, int code, int dstCn=0, AlgorithmHint hint=cv::ALGO_HINT_DEFAULT)
	将图像从一种颜色空间转换为另一种颜色空间。

void	cv::cvtColorTwoPlane (InputArray src1, InputArray src2, OutputArray dst, int code, AlgorithmHint hint=cv::ALGO_HINT_DEFAULT)
	将图像从一种颜色空间转换为另一种颜色空间，其中源图像存储在两个平面中。

void	cv::demosaicing (InputArray src, OutputArray dst, int code, int dstCn=0)
	所有去马赛克过程的主函数

void	cv::dilate (InputArray src, OutputArray dst, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
	使用特定的结构元素膨胀图像。

void	cv::distanceTransform (InputArray src, OutputArray dst, int distanceType, int maskSize, int dstType=CV_32F)

void	cv::distanceTransform (InputArray src, OutputArray dst, OutputArray labels, int distanceType, int maskSize, int labelType=DIST_LABEL_CCOMP)
	计算源图像每个像素到最近零像素的距离。

void	cv::divSpectrums (InputArray a, InputArray b, OutputArray c, int flags, bool conjB=false)
	执行第一个傅里叶频谱与第二个傅里叶频谱的逐元素除法。

void	cv::drawContours (InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar &color, int thickness=1, int lineType=LINE_8, InputArray hierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point())
	绘制轮廓轮廓或填充轮廓。

void	cv::drawMarker (InputOutputArray img, Point position, const Scalar &color, int markerType=MARKER_CROSS, int markerSize=20, int thickness=1, int line_type=8)
	在图像的预定义位置绘制标记。

void	cv::ellipse (InputOutputArray img, const RotatedRect &box, const Scalar &color, int thickness=1, int lineType=LINE_8)

void	cv::ellipse (InputOutputArray img, Point center, Size axes, double angle, double startAngle, double endAngle, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
	绘制简单的或粗的椭圆弧或填充椭圆扇区。

void	cv::ellipse2Poly (Point center, Size axes, int angle, int arcStart, int arcEnd, int delta, std::vector< Point > &pts)
	用折线逼近椭圆弧。

void	cv::ellipse2Poly (Point2d center, Size2d axes, int angle, int arcStart, int arcEnd, int delta, std::vector< Point2d > &pts)

float	cv::EMD (InputArray signature1, InputArray signature2, int distType, InputArray cost=noArray(), float *lowerBound=0, OutputArray flow=noArray())
	计算两个加权点配置之间的“最小工作”距离。

void	cv::equalizeHist (InputArray src, OutputArray dst)
	均衡灰度图像的直方图。

void	cv::erode (InputArray src, OutputArray dst, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
	使用特定的结构元素腐蚀图像。

void	cv::fillConvexPoly (InputOutputArray img, const Point *pts, int npts, const Scalar &color, int lineType=LINE_8, int shift=0)

void	cv::fillConvexPoly (InputOutputArray img, InputArray points, const Scalar &color, int lineType=LINE_8, int shift=0)
	填充凸多边形。

void	cv::fillPoly (InputOutputArray img, const Point *pts, const int npts, int ncontours, const Scalar &color, int lineType=LINE_8, int shift=0, Point offset=Point())

void	cv::fillPoly (InputOutputArray img, InputArrayOfArrays pts, const Scalar &color, int lineType=LINE_8, int shift=0, Point offset=Point())
	填充一个或多个多边形包围的区域。

void	cv::filter2D (InputArray src, OutputArray dst, int ddepth, InputArray kernel, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT)
	用内核卷积图像。

void	cv::findContours (InputArray image, OutputArrayOfArrays contours, int mode, int method, Point offset=Point())

void	cv::findContours (InputArray image, OutputArrayOfArrays contours, OutputArray hierarchy, int mode, int method, Point offset=Point())
	在二值图像中查找轮廓。

void	cv::findContoursLinkRuns (InputArray image, OutputArrayOfArrays contours)
	这是一个重载的成员函数，为了方便提供。它与上面的函数的区别仅仅在于它接受的参数。

void	cv::findContoursLinkRuns (InputArray image, OutputArrayOfArrays contours, OutputArray hierarchy)
	使用链接运行算法查找轮廓。

RotatedRect	cv::fitEllipse (InputArray points)
	拟合一组二维点周围的椭圆。

RotatedRect	cv::fitEllipseAMS (InputArray points)
	拟合一组二维点周围的椭圆。

RotatedRect	cv::fitEllipseDirect (InputArray points)
	拟合一组二维点周围的椭圆。

void	cv::fitLine (InputArray points, OutputArray line, int distType, double param, double reps, double aeps)
	将直线拟合到二维或三维点集。

int	cv::floodFill (InputOutputArray image, InputOutputArray mask, Point seedPoint, Scalar newVal, Rect *rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4)
	用给定颜色填充连通分量。

int	cv::floodFill (InputOutputArray image, Point seedPoint, Scalar newVal, Rect *rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4)

void	cv::GaussianBlur (InputArray src, OutputArray dst, Size ksize, double sigmaX, double sigmaY=0, int borderType=BORDER_DEFAULT, AlgorithmHint hint=cv::ALGO_HINT_DEFAULT)
	使用高斯滤波器模糊图像。

Mat	cv::getAffineTransform (const Point2f src[], const Point2f dst[])
	根据三对对应点计算仿射变换。

Mat	cv::getAffineTransform (InputArray src, InputArray dst)

void	cv::getDerivKernels (OutputArray kx, OutputArray ky, int dx, int dy, int ksize, bool normalize=false, int ktype=CV_32F)
	返回用于计算空间图像导数的滤波器系数。

double	cv::getFontScaleFromHeight (const int fontFace, const int pixelHeight, const int thickness=1)
	计算字体大小以达到给定的像素高度。

Mat	cv::getGaborKernel (Size ksize, double sigma, double theta, double lambd, double gamma, double psi=CV_PI *0.5, int ktype=CV_64F)
	返回 Gabor 滤波器系数。

Mat	cv::getGaussianKernel (int ksize, double sigma, int ktype=CV_64F)
	返回高斯滤波器系数。

Mat	cv::getPerspectiveTransform (const Point2f src[], const Point2f dst[], int solveMethod=DECOMP_LU)

Mat	cv::getPerspectiveTransform (InputArray src, InputArray dst, int solveMethod=DECOMP_LU)
	根据四对对应点计算透视变换。

void	cv::getRectSubPix (InputArray image, Size patchSize, Point2f center, OutputArray patch, int patchType=-1)
	以亚像素精度从图像中检索像素矩形。

Mat	cv::getRotationMatrix2D (Point2f center, double angle, double scale)
	计算二维旋转的仿射矩阵。

Matx23d	cv::getRotationMatrix2D_ (Point2f center, double angle, double scale)

Mat	cv::getStructuringElement (int shape, Size ksize, Point anchor=Point(-1,-1))
	返回指定大小和形状的结构元素，用于形态学运算。

Size	cv::getTextSize (const String &text, int fontFace, double fontScale, int thickness, int *baseLine)
	计算文本字符串的宽度和高度。

void	cv::goodFeaturesToTrack (InputArray image, OutputArray corners, int maxCorners, double qualityLevel, double minDistance, InputArray mask, int blockSize, int gradientSize, bool useHarrisDetector=false, double k=0.04)

void	cv::goodFeaturesToTrack (InputArray image, OutputArray corners, int maxCorners, double qualityLevel, double minDistance, InputArray mask, OutputArray cornersQuality, int blockSize=3, int gradientSize=3, bool useHarrisDetector=false, double k=0.04)
	与上面相同，但同时也返回检测到的角点的质量度量。

void	cv::goodFeaturesToTrack (InputArray image, OutputArray corners, int maxCorners, double qualityLevel, double minDistance, InputArray mask=noArray(), int blockSize=3, bool useHarrisDetector=false, double k=0.04)
	确定图像上的强角点。

void	cv::grabCut (InputArray img, InputOutputArray mask, Rect rect, InputOutputArray bgdModel, InputOutputArray fgdModel, int iterCount, int mode=GC_EVAL)
	运行 GrabCut 算法。

void	cv::HoughCircles (InputArray image, OutputArray circles, int method, double dp, double minDist, double param1=100, double param2=100, int minRadius=0, int maxRadius=0)
	使用霍夫变换在灰度图像中查找圆圈。

void	cv::HoughLines (InputArray image, OutputArray lines, double rho, double theta, int threshold, double srn=0, double stn=0, double min_theta=0, double max_theta=CV_PI, bool use_edgeval=false)
	使用标准霍夫变换在二值图像中查找直线。

void	cv::HoughLinesP (InputArray image, OutputArray lines, double rho, double theta, int threshold, double minLineLength=0, double maxLineGap=0)
	使用概率霍夫变换在二值图像中查找线段。

void	cv::HoughLinesPointSet (InputArray point, OutputArray lines, int lines_max, int threshold, double min_rho, double max_rho, double rho_step, double min_theta, double max_theta, double theta_step)
	使用标准霍夫变换查找点集中的直线。

void	cv::HuMoments (const Moments &m, OutputArray hu)

void	cv::HuMoments (const Moments &moments, double hu[7])
	计算七个Hu不变矩。

void	cv::integral (InputArray src, OutputArray sum, int sdepth=-1)

void	cv::integral (InputArray src, OutputArray sum, OutputArray sqsum, int sdepth=-1, int sqdepth=-1)

void	cv::integral (InputArray src, OutputArray sum, OutputArray sqsum, OutputArray tilted, int sdepth=-1, int sqdepth=-1)
	计算图像的积分。

float	cv::intersectConvexConvex (InputArray p1, InputArray p2, OutputArray p12, bool handleNested=true)
	查找两个凸多边形的交集。

void	cv::invertAffineTransform (InputArray M, OutputArray iM)
	反转仿射变换。

bool	cv::isContourConvex (InputArray contour)
	测试轮廓的凸性。

void	cv::Laplacian (InputArray src, OutputArray dst, int ddepth, int ksize=1, double scale=1, double delta=0, int borderType=BORDER_DEFAULT)
	计算图像的拉普拉斯算子。

void	cv::line (InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
	绘制连接两点的线段。

void	cv::linearPolar (InputArray src, OutputArray dst, Point2f center, double maxRadius, int flags)
	将图像重新映射到极坐标空间。

void	cv::logPolar (InputArray src, OutputArray dst, Point2f center, double M, int flags)
	将图像重新映射到半对数极坐标空间。

double	cv::matchShapes (InputArray contour1, InputArray contour2, int method, double parameter)
	比较两个形状。

void	cv::matchTemplate (InputArray image, InputArray templ, OutputArray result, int method, InputArray mask=noArray())
	将模板与重叠的图像区域进行比较。

void	cv::medianBlur (InputArray src, OutputArray dst, int ksize)
	使用中值滤波器模糊图像。

RotatedRect	cv::minAreaRect (InputArray points)
	查找包含输入二维点集的最小面积旋转矩形。

void	cv::minEnclosingCircle (InputArray points, Point2f &center, float &radius)
	查找包含二维点集的最小面积圆。

double	cv::minEnclosingTriangle (InputArray points, OutputArray triangle)
	查找包含二维点集的最小面积三角形并返回其面积。

Moments	cv::moments (InputArray array, bool binaryImage=false)
	计算多边形或光栅化形状最多三阶的所有矩。

static Scalar	cv::morphologyDefaultBorderValue ()
	返回腐蚀和膨胀的“魔术”边界值。它会自动转换为Scalar::all(-DBL_MAX) 用于膨胀。

void	cv::morphologyEx (InputArray src, OutputArray dst, int op, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
	执行高级形态学变换。

Point2d	cv::phaseCorrelate (InputArray src1, InputArray src2, InputArray window=noArray(), double *response=0)
	该函数用于检测两幅图像之间发生的平移位移。

double	cv::pointPolygonTest (InputArray contour, Point2f pt, bool measureDist)
	执行点-轮廓测试。

void	cv::polylines (InputOutputArray img, const Point const pts, const int *npts, int ncontours, bool isClosed, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)

void	cv::polylines (InputOutputArray img, InputArrayOfArrays pts, bool isClosed, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
	绘制多条多边曲线。

void	cv::preCornerDetect (InputArray src, OutputArray dst, int ksize, int borderType=BORDER_DEFAULT)
	计算角点检测的特征图。

void	cv::putText (InputOutputArray img, const String &text, Point org, int fontFace, double fontScale, Scalar color, int thickness=1, int lineType=LINE_8, bool bottomLeftOrigin=false)
	绘制文本字符串。

void	cv::pyrDown (InputArray src, OutputArray dst, const Size &dstsize=Size(), int borderType=BORDER_DEFAULT)
	模糊图像并对其进行下采样。

void	cv::pyrMeanShiftFiltering (InputArray src, OutputArray dst, double sp, double sr, int maxLevel=1, TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1))
	执行图像均值漂移分割的初始步骤。

void	cv::pyrUp (InputArray src, OutputArray dst, const Size &dstsize=Size(), int borderType=BORDER_DEFAULT)
	对图像进行上采样，然后对其进行模糊处理。

void	cv::rectangle (InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
	绘制一个简单的、粗的或填充的右上矩形。

void	cv::rectangle (InputOutputArray img, Rect rec, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)

void	cv::remap (InputArray src, OutputArray dst, InputArray map1, InputArray map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	将通用几何变换应用于图像。

void	cv::resize (InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR)
	调整图像大小。

int	cv::rotatedRectangleIntersection (const RotatedRect &rect1, const RotatedRect &rect2, OutputArray intersectingRegion)
	找出两个旋转矩形之间是否存在任何交集。

void	cv::Scharr (InputArray src, OutputArray dst, int ddepth, int dx, int dy, double scale=1, double delta=0, int borderType=BORDER_DEFAULT)
	使用 Scharr 算子计算图像的 x 或 y 方向的一阶导数。

void	cv::sepFilter2D (InputArray src, OutputArray dst, int ddepth, InputArray kernelX, InputArray kernelY, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT)
	对图像应用可分离线性滤波器。

void	cv::Sobel (InputArray src, OutputArray dst, int ddepth, int dx, int dy, int ksize=3, double scale=1, double delta=0, int borderType=BORDER_DEFAULT)
	使用扩展的 Sobel 算子计算图像的一阶、二阶、三阶或混合导数。

void	cv::spatialGradient (InputArray src, OutputArray dx, OutputArray dy, int ksize=3, int borderType=BORDER_DEFAULT)
	使用 Sobel 算子计算图像在 x 和 y 方向上的一阶导数。

void	cv::sqrBoxFilter (InputArray src, OutputArray dst, int ddepth, Size ksize, Point anchor=Point(-1, -1), bool normalize=true, int borderType=BORDER_DEFAULT)
	计算与滤波器重叠的像素值的平方和的归一化值。

void	cv::stackBlur (InputArray src, OutputArray dst, Size ksize)
	使用 stackBlur 模糊图像。

double	cv::threshold (InputArray src, OutputArray dst, double thresh, double maxval, int type)
	对每个数组元素应用固定级别的阈值。

void	cv::warpAffine (InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	对图像应用仿射变换。

void	cv::warpPerspective (InputArray src, OutputArray dst, InputArray M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	对图像应用透视变换。

void	cv::warpPolar (InputArray src, OutputArray dst, Size dsize, Point2f center, double maxRadius, int flags)
	将图像重新映射到极坐标或半对数极坐标空间。

void	cv::watershed (InputArray image, InputOutputArray markers)
	使用分水岭算法执行基于标记的图像分割。

float	cv::wrapperEMD (InputArray signature1, InputArray signature2, int distType, InputArray cost=noArray(), Ptr< float > lowerBound=Ptr< float >(), OutputArray flow=noArray())

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