1 /*M/////////////////////////////////////////////////////////////////////////////////////// 2 // 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. 4 // 5 // By downloading, copying, installing or using the software you agree to this license. 6 // If you do not agree to this license, do not download, install, 7 // copy or use the software. 8 // 9 // 10 // License Agreement 11 // For Open Source Computer Vision Library 12 // 13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. 14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved. 15 // Third party copyrights are property of their respective owners. 16 // 17 // Redistribution and use in source and binary forms, with or without modification, 18 // are permitted provided that the following conditions are met: 19 // 20 // * Redistribution's of source code must retain the above copyright notice, 21 // this list of conditions and the following disclaimer. 22 // 23 // * Redistribution's in binary form must reproduce the above copyright notice, 24 // this list of conditions and the following disclaimer in the documentation 25 // and/or other materials provided with the distribution. 26 // 27 // * The name of the copyright holders may not be used to endorse or promote products 28 // derived from this software without specific prior written permission. 29 // 30 // This software is provided by the copyright holders and contributors "as is" and 31 // any express or implied warranties, including, but not limited to, the implied 32 // warranties of merchantability and fitness for a particular purpose are disclaimed. 33 // In no event shall the Intel Corporation or contributors be liable for any direct, 34 // indirect, incidental, special, exemplary, or consequential damages 35 // (including, but not limited to, procurement of substitute goods or services; 36 // loss of use, data, or profits; or business interruption) however caused 37 // and on any theory of liability, whether in contract, strict liability, 38 // or tort (including negligence or otherwise) arising in any way out of 39 // the use of this software, even if advised of the possibility of such damage. 40 // 41 //M*/ 42 43 #ifndef __OPENCV_IMGPROC_TYPES_C_H__ 44 #define __OPENCV_IMGPROC_TYPES_C_H__ 45 46 #include "opencv2/core/core_c.h" 47 48 #ifdef __cplusplus 49 extern "C" { 50 #endif 51 52 /** @addtogroup imgproc_c 53 @{ 54 */ 55 56 /** Connected component structure */ 57 typedef struct CvConnectedComp 58 { 59 double area; /**<area of the connected component */ 60 CvScalar value; /**<average color of the connected component */ 61 CvRect rect; /**<ROI of the component */ 62 CvSeq* contour; /**<optional component boundary 63 (the contour might have child contours corresponding to the holes)*/ 64 } 65 CvConnectedComp; 66 67 /** Image smooth methods */ 68 enum SmoothMethod_c 69 { 70 /** linear convolution with \f$\texttt{size1}\times\texttt{size2}\f$ box kernel (all 1's). If 71 you want to smooth different pixels with different-size box kernels, you can use the integral 72 image that is computed using integral */ 73 CV_BLUR_NO_SCALE =0, 74 /** linear convolution with \f$\texttt{size1}\times\texttt{size2}\f$ box kernel (all 75 1's) with subsequent scaling by \f$1/(\texttt{size1}\cdot\texttt{size2})\f$ */ 76 CV_BLUR =1, 77 /** linear convolution with a \f$\texttt{size1}\times\texttt{size2}\f$ Gaussian kernel */ 78 CV_GAUSSIAN =2, 79 /** median filter with a \f$\texttt{size1}\times\texttt{size1}\f$ square aperture */ 80 CV_MEDIAN =3, 81 /** bilateral filter with a \f$\texttt{size1}\times\texttt{size1}\f$ square aperture, color 82 sigma= sigma1 and spatial sigma= sigma2. If size1=0, the aperture square side is set to 83 cvRound(sigma2\*1.5)\*2+1. See cv::bilateralFilter */ 84 CV_BILATERAL =4 85 }; 86 87 /** Filters used in pyramid decomposition */ 88 enum 89 { 90 CV_GAUSSIAN_5x5 = 7 91 }; 92 93 /** Special filters */ 94 enum 95 { 96 CV_SCHARR =-1, 97 CV_MAX_SOBEL_KSIZE =7 98 }; 99 100 /** Constants for color conversion */ 101 enum 102 { 103 CV_BGR2BGRA =0, 104 CV_RGB2RGBA =CV_BGR2BGRA, 105 106 CV_BGRA2BGR =1, 107 CV_RGBA2RGB =CV_BGRA2BGR, 108 109 CV_BGR2RGBA =2, 110 CV_RGB2BGRA =CV_BGR2RGBA, 111 112 CV_RGBA2BGR =3, 113 CV_BGRA2RGB =CV_RGBA2BGR, 114 115 CV_BGR2RGB =4, 116 CV_RGB2BGR =CV_BGR2RGB, 117 118 CV_BGRA2RGBA =5, 119 CV_RGBA2BGRA =CV_BGRA2RGBA, 120 121 CV_BGR2GRAY =6, 122 CV_RGB2GRAY =7, 123 CV_GRAY2BGR =8, 124 CV_GRAY2RGB =CV_GRAY2BGR, 125 CV_GRAY2BGRA =9, 126 CV_GRAY2RGBA =CV_GRAY2BGRA, 127 CV_BGRA2GRAY =10, 128 CV_RGBA2GRAY =11, 129 130 CV_BGR2BGR565 =12, 131 CV_RGB2BGR565 =13, 132 CV_BGR5652BGR =14, 133 CV_BGR5652RGB =15, 134 CV_BGRA2BGR565 =16, 135 CV_RGBA2BGR565 =17, 136 CV_BGR5652BGRA =18, 137 CV_BGR5652RGBA =19, 138 139 CV_GRAY2BGR565 =20, 140 CV_BGR5652GRAY =21, 141 142 CV_BGR2BGR555 =22, 143 CV_RGB2BGR555 =23, 144 CV_BGR5552BGR =24, 145 CV_BGR5552RGB =25, 146 CV_BGRA2BGR555 =26, 147 CV_RGBA2BGR555 =27, 148 CV_BGR5552BGRA =28, 149 CV_BGR5552RGBA =29, 150 151 CV_GRAY2BGR555 =30, 152 CV_BGR5552GRAY =31, 153 154 CV_BGR2XYZ =32, 155 CV_RGB2XYZ =33, 156 CV_XYZ2BGR =34, 157 CV_XYZ2RGB =35, 158 159 CV_BGR2YCrCb =36, 160 CV_RGB2YCrCb =37, 161 CV_YCrCb2BGR =38, 162 CV_YCrCb2RGB =39, 163 164 CV_BGR2HSV =40, 165 CV_RGB2HSV =41, 166 167 CV_BGR2Lab =44, 168 CV_RGB2Lab =45, 169 170 CV_BayerBG2BGR =46, 171 CV_BayerGB2BGR =47, 172 CV_BayerRG2BGR =48, 173 CV_BayerGR2BGR =49, 174 175 CV_BayerBG2RGB =CV_BayerRG2BGR, 176 CV_BayerGB2RGB =CV_BayerGR2BGR, 177 CV_BayerRG2RGB =CV_BayerBG2BGR, 178 CV_BayerGR2RGB =CV_BayerGB2BGR, 179 180 CV_BGR2Luv =50, 181 CV_RGB2Luv =51, 182 CV_BGR2HLS =52, 183 CV_RGB2HLS =53, 184 185 CV_HSV2BGR =54, 186 CV_HSV2RGB =55, 187 188 CV_Lab2BGR =56, 189 CV_Lab2RGB =57, 190 CV_Luv2BGR =58, 191 CV_Luv2RGB =59, 192 CV_HLS2BGR =60, 193 CV_HLS2RGB =61, 194 195 CV_BayerBG2BGR_VNG =62, 196 CV_BayerGB2BGR_VNG =63, 197 CV_BayerRG2BGR_VNG =64, 198 CV_BayerGR2BGR_VNG =65, 199 200 CV_BayerBG2RGB_VNG =CV_BayerRG2BGR_VNG, 201 CV_BayerGB2RGB_VNG =CV_BayerGR2BGR_VNG, 202 CV_BayerRG2RGB_VNG =CV_BayerBG2BGR_VNG, 203 CV_BayerGR2RGB_VNG =CV_BayerGB2BGR_VNG, 204 205 CV_BGR2HSV_FULL = 66, 206 CV_RGB2HSV_FULL = 67, 207 CV_BGR2HLS_FULL = 68, 208 CV_RGB2HLS_FULL = 69, 209 210 CV_HSV2BGR_FULL = 70, 211 CV_HSV2RGB_FULL = 71, 212 CV_HLS2BGR_FULL = 72, 213 CV_HLS2RGB_FULL = 73, 214 215 CV_LBGR2Lab = 74, 216 CV_LRGB2Lab = 75, 217 CV_LBGR2Luv = 76, 218 CV_LRGB2Luv = 77, 219 220 CV_Lab2LBGR = 78, 221 CV_Lab2LRGB = 79, 222 CV_Luv2LBGR = 80, 223 CV_Luv2LRGB = 81, 224 225 CV_BGR2YUV = 82, 226 CV_RGB2YUV = 83, 227 CV_YUV2BGR = 84, 228 CV_YUV2RGB = 85, 229 230 CV_BayerBG2GRAY = 86, 231 CV_BayerGB2GRAY = 87, 232 CV_BayerRG2GRAY = 88, 233 CV_BayerGR2GRAY = 89, 234 235 //YUV 4:2:0 formats family 236 CV_YUV2RGB_NV12 = 90, 237 CV_YUV2BGR_NV12 = 91, 238 CV_YUV2RGB_NV21 = 92, 239 CV_YUV2BGR_NV21 = 93, 240 CV_YUV420sp2RGB = CV_YUV2RGB_NV21, 241 CV_YUV420sp2BGR = CV_YUV2BGR_NV21, 242 243 CV_YUV2RGBA_NV12 = 94, 244 CV_YUV2BGRA_NV12 = 95, 245 CV_YUV2RGBA_NV21 = 96, 246 CV_YUV2BGRA_NV21 = 97, 247 CV_YUV420sp2RGBA = CV_YUV2RGBA_NV21, 248 CV_YUV420sp2BGRA = CV_YUV2BGRA_NV21, 249 250 CV_YUV2RGB_YV12 = 98, 251 CV_YUV2BGR_YV12 = 99, 252 CV_YUV2RGB_IYUV = 100, 253 CV_YUV2BGR_IYUV = 101, 254 CV_YUV2RGB_I420 = CV_YUV2RGB_IYUV, 255 CV_YUV2BGR_I420 = CV_YUV2BGR_IYUV, 256 CV_YUV420p2RGB = CV_YUV2RGB_YV12, 257 CV_YUV420p2BGR = CV_YUV2BGR_YV12, 258 259 CV_YUV2RGBA_YV12 = 102, 260 CV_YUV2BGRA_YV12 = 103, 261 CV_YUV2RGBA_IYUV = 104, 262 CV_YUV2BGRA_IYUV = 105, 263 CV_YUV2RGBA_I420 = CV_YUV2RGBA_IYUV, 264 CV_YUV2BGRA_I420 = CV_YUV2BGRA_IYUV, 265 CV_YUV420p2RGBA = CV_YUV2RGBA_YV12, 266 CV_YUV420p2BGRA = CV_YUV2BGRA_YV12, 267 268 CV_YUV2GRAY_420 = 106, 269 CV_YUV2GRAY_NV21 = CV_YUV2GRAY_420, 270 CV_YUV2GRAY_NV12 = CV_YUV2GRAY_420, 271 CV_YUV2GRAY_YV12 = CV_YUV2GRAY_420, 272 CV_YUV2GRAY_IYUV = CV_YUV2GRAY_420, 273 CV_YUV2GRAY_I420 = CV_YUV2GRAY_420, 274 CV_YUV420sp2GRAY = CV_YUV2GRAY_420, 275 CV_YUV420p2GRAY = CV_YUV2GRAY_420, 276 277 //YUV 4:2:2 formats family 278 CV_YUV2RGB_UYVY = 107, 279 CV_YUV2BGR_UYVY = 108, 280 //CV_YUV2RGB_VYUY = 109, 281 //CV_YUV2BGR_VYUY = 110, 282 CV_YUV2RGB_Y422 = CV_YUV2RGB_UYVY, 283 CV_YUV2BGR_Y422 = CV_YUV2BGR_UYVY, 284 CV_YUV2RGB_UYNV = CV_YUV2RGB_UYVY, 285 CV_YUV2BGR_UYNV = CV_YUV2BGR_UYVY, 286 287 CV_YUV2RGBA_UYVY = 111, 288 CV_YUV2BGRA_UYVY = 112, 289 //CV_YUV2RGBA_VYUY = 113, 290 //CV_YUV2BGRA_VYUY = 114, 291 CV_YUV2RGBA_Y422 = CV_YUV2RGBA_UYVY, 292 CV_YUV2BGRA_Y422 = CV_YUV2BGRA_UYVY, 293 CV_YUV2RGBA_UYNV = CV_YUV2RGBA_UYVY, 294 CV_YUV2BGRA_UYNV = CV_YUV2BGRA_UYVY, 295 296 CV_YUV2RGB_YUY2 = 115, 297 CV_YUV2BGR_YUY2 = 116, 298 CV_YUV2RGB_YVYU = 117, 299 CV_YUV2BGR_YVYU = 118, 300 CV_YUV2RGB_YUYV = CV_YUV2RGB_YUY2, 301 CV_YUV2BGR_YUYV = CV_YUV2BGR_YUY2, 302 CV_YUV2RGB_YUNV = CV_YUV2RGB_YUY2, 303 CV_YUV2BGR_YUNV = CV_YUV2BGR_YUY2, 304 305 CV_YUV2RGBA_YUY2 = 119, 306 CV_YUV2BGRA_YUY2 = 120, 307 CV_YUV2RGBA_YVYU = 121, 308 CV_YUV2BGRA_YVYU = 122, 309 CV_YUV2RGBA_YUYV = CV_YUV2RGBA_YUY2, 310 CV_YUV2BGRA_YUYV = CV_YUV2BGRA_YUY2, 311 CV_YUV2RGBA_YUNV = CV_YUV2RGBA_YUY2, 312 CV_YUV2BGRA_YUNV = CV_YUV2BGRA_YUY2, 313 314 CV_YUV2GRAY_UYVY = 123, 315 CV_YUV2GRAY_YUY2 = 124, 316 //CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY, 317 CV_YUV2GRAY_Y422 = CV_YUV2GRAY_UYVY, 318 CV_YUV2GRAY_UYNV = CV_YUV2GRAY_UYVY, 319 CV_YUV2GRAY_YVYU = CV_YUV2GRAY_YUY2, 320 CV_YUV2GRAY_YUYV = CV_YUV2GRAY_YUY2, 321 CV_YUV2GRAY_YUNV = CV_YUV2GRAY_YUY2, 322 323 // alpha premultiplication 324 CV_RGBA2mRGBA = 125, 325 CV_mRGBA2RGBA = 126, 326 327 CV_RGB2YUV_I420 = 127, 328 CV_BGR2YUV_I420 = 128, 329 CV_RGB2YUV_IYUV = CV_RGB2YUV_I420, 330 CV_BGR2YUV_IYUV = CV_BGR2YUV_I420, 331 332 CV_RGBA2YUV_I420 = 129, 333 CV_BGRA2YUV_I420 = 130, 334 CV_RGBA2YUV_IYUV = CV_RGBA2YUV_I420, 335 CV_BGRA2YUV_IYUV = CV_BGRA2YUV_I420, 336 CV_RGB2YUV_YV12 = 131, 337 CV_BGR2YUV_YV12 = 132, 338 CV_RGBA2YUV_YV12 = 133, 339 CV_BGRA2YUV_YV12 = 134, 340 341 // Edge-Aware Demosaicing 342 CV_BayerBG2BGR_EA = 135, 343 CV_BayerGB2BGR_EA = 136, 344 CV_BayerRG2BGR_EA = 137, 345 CV_BayerGR2BGR_EA = 138, 346 347 CV_BayerBG2RGB_EA = CV_BayerRG2BGR_EA, 348 CV_BayerGB2RGB_EA = CV_BayerGR2BGR_EA, 349 CV_BayerRG2RGB_EA = CV_BayerBG2BGR_EA, 350 CV_BayerGR2RGB_EA = CV_BayerGB2BGR_EA, 351 352 CV_COLORCVT_MAX = 139 353 }; 354 355 356 /** Sub-pixel interpolation methods */ 357 enum 358 { 359 CV_INTER_NN =0, 360 CV_INTER_LINEAR =1, 361 CV_INTER_CUBIC =2, 362 CV_INTER_AREA =3, 363 CV_INTER_LANCZOS4 =4 364 }; 365 366 /** ... and other image warping flags */ 367 enum 368 { 369 CV_WARP_FILL_OUTLIERS =8, 370 CV_WARP_INVERSE_MAP =16 371 }; 372 373 /** Shapes of a structuring element for morphological operations 374 @see cv::MorphShapes, cv::getStructuringElement 375 */ 376 enum MorphShapes_c 377 { 378 CV_SHAPE_RECT =0, 379 CV_SHAPE_CROSS =1, 380 CV_SHAPE_ELLIPSE =2, 381 CV_SHAPE_CUSTOM =100 //!< custom structuring element 382 }; 383 384 /** Morphological operations */ 385 enum 386 { 387 CV_MOP_ERODE =0, 388 CV_MOP_DILATE =1, 389 CV_MOP_OPEN =2, 390 CV_MOP_CLOSE =3, 391 CV_MOP_GRADIENT =4, 392 CV_MOP_TOPHAT =5, 393 CV_MOP_BLACKHAT =6 394 }; 395 396 /** Spatial and central moments */ 397 typedef struct CvMoments 398 { 399 double m00, m10, m01, m20, m11, m02, m30, m21, m12, m03; /**< spatial moments */ 400 double mu20, mu11, mu02, mu30, mu21, mu12, mu03; /**< central moments */ 401 double inv_sqrt_m00; /**< m00 != 0 ? 1/sqrt(m00) : 0 */ 402 403 #ifdef __cplusplus CvMomentsCvMoments404 CvMoments(){} CvMomentsCvMoments405 CvMoments(const cv::Moments& m) 406 { 407 m00 = m.m00; m10 = m.m10; m01 = m.m01; 408 m20 = m.m20; m11 = m.m11; m02 = m.m02; 409 m30 = m.m30; m21 = m.m21; m12 = m.m12; m03 = m.m03; 410 mu20 = m.mu20; mu11 = m.mu11; mu02 = m.mu02; 411 mu30 = m.mu30; mu21 = m.mu21; mu12 = m.mu12; mu03 = m.mu03; 412 double am00 = std::abs(m.m00); 413 inv_sqrt_m00 = am00 > DBL_EPSILON ? 1./std::sqrt(am00) : 0; 414 } MomentsCvMoments415 operator cv::Moments() const 416 { 417 return cv::Moments(m00, m10, m01, m20, m11, m02, m30, m21, m12, m03); 418 } 419 #endif 420 } 421 CvMoments; 422 423 /** Hu invariants */ 424 typedef struct CvHuMoments 425 { 426 double hu1, hu2, hu3, hu4, hu5, hu6, hu7; /**< Hu invariants */ 427 } 428 CvHuMoments; 429 430 /** Template matching methods */ 431 enum 432 { 433 CV_TM_SQDIFF =0, 434 CV_TM_SQDIFF_NORMED =1, 435 CV_TM_CCORR =2, 436 CV_TM_CCORR_NORMED =3, 437 CV_TM_CCOEFF =4, 438 CV_TM_CCOEFF_NORMED =5 439 }; 440 441 typedef float (CV_CDECL * CvDistanceFunction)( const float* a, const float* b, void* user_param ); 442 443 /** Contour retrieval modes */ 444 enum 445 { 446 CV_RETR_EXTERNAL=0, 447 CV_RETR_LIST=1, 448 CV_RETR_CCOMP=2, 449 CV_RETR_TREE=3, 450 CV_RETR_FLOODFILL=4 451 }; 452 453 /** Contour approximation methods */ 454 enum 455 { 456 CV_CHAIN_CODE=0, 457 CV_CHAIN_APPROX_NONE=1, 458 CV_CHAIN_APPROX_SIMPLE=2, 459 CV_CHAIN_APPROX_TC89_L1=3, 460 CV_CHAIN_APPROX_TC89_KCOS=4, 461 CV_LINK_RUNS=5 462 }; 463 464 /* 465 Internal structure that is used for sequential retrieving contours from the image. 466 It supports both hierarchical and plane variants of Suzuki algorithm. 467 */ 468 typedef struct _CvContourScanner* CvContourScanner; 469 470 /** Freeman chain reader state */ 471 typedef struct CvChainPtReader 472 { 473 CV_SEQ_READER_FIELDS() 474 char code; 475 CvPoint pt; 476 schar deltas[8][2]; 477 } 478 CvChainPtReader; 479 480 /** initializes 8-element array for fast access to 3x3 neighborhood of a pixel */ 481 #define CV_INIT_3X3_DELTAS( deltas, step, nch ) \ 482 ((deltas)[0] = (nch), (deltas)[1] = -(step) + (nch), \ 483 (deltas)[2] = -(step), (deltas)[3] = -(step) - (nch), \ 484 (deltas)[4] = -(nch), (deltas)[5] = (step) - (nch), \ 485 (deltas)[6] = (step), (deltas)[7] = (step) + (nch)) 486 487 488 /** Contour approximation algorithms */ 489 enum 490 { 491 CV_POLY_APPROX_DP = 0 492 }; 493 494 /** @brief Shape matching methods 495 496 \f$A\f$ denotes object1,\f$B\f$ denotes object2 497 498 \f$\begin{array}{l} m^A_i = \mathrm{sign} (h^A_i) \cdot \log{h^A_i} \\ m^B_i = \mathrm{sign} (h^B_i) \cdot \log{h^B_i} \end{array}\f$ 499 500 and \f$h^A_i, h^B_i\f$ are the Hu moments of \f$A\f$ and \f$B\f$ , respectively. 501 */ 502 enum ShapeMatchModes 503 { 504 CV_CONTOURS_MATCH_I1 =1, //!< \f[I_1(A,B) = \sum _{i=1...7} \left | \frac{1}{m^A_i} - \frac{1}{m^B_i} \right |\f] 505 CV_CONTOURS_MATCH_I2 =2, //!< \f[I_2(A,B) = \sum _{i=1...7} \left | m^A_i - m^B_i \right |\f] 506 CV_CONTOURS_MATCH_I3 =3 //!< \f[I_3(A,B) = \max _{i=1...7} \frac{ \left| m^A_i - m^B_i \right| }{ \left| m^A_i \right| }\f] 507 }; 508 509 /** Shape orientation */ 510 enum 511 { 512 CV_CLOCKWISE =1, 513 CV_COUNTER_CLOCKWISE =2 514 }; 515 516 517 /** Convexity defect */ 518 typedef struct CvConvexityDefect 519 { 520 CvPoint* start; /**< point of the contour where the defect begins */ 521 CvPoint* end; /**< point of the contour where the defect ends */ 522 CvPoint* depth_point; /**< the farthest from the convex hull point within the defect */ 523 float depth; /**< distance between the farthest point and the convex hull */ 524 } CvConvexityDefect; 525 526 527 /** Histogram comparison methods */ 528 enum 529 { 530 CV_COMP_CORREL =0, 531 CV_COMP_CHISQR =1, 532 CV_COMP_INTERSECT =2, 533 CV_COMP_BHATTACHARYYA =3, 534 CV_COMP_HELLINGER =CV_COMP_BHATTACHARYYA, 535 CV_COMP_CHISQR_ALT =4, 536 CV_COMP_KL_DIV =5 537 }; 538 539 /** Mask size for distance transform */ 540 enum 541 { 542 CV_DIST_MASK_3 =3, 543 CV_DIST_MASK_5 =5, 544 CV_DIST_MASK_PRECISE =0 545 }; 546 547 /** Content of output label array: connected components or pixels */ 548 enum 549 { 550 CV_DIST_LABEL_CCOMP = 0, 551 CV_DIST_LABEL_PIXEL = 1 552 }; 553 554 /** Distance types for Distance Transform and M-estimators */ 555 enum 556 { 557 CV_DIST_USER =-1, /**< User defined distance */ 558 CV_DIST_L1 =1, /**< distance = |x1-x2| + |y1-y2| */ 559 CV_DIST_L2 =2, /**< the simple euclidean distance */ 560 CV_DIST_C =3, /**< distance = max(|x1-x2|,|y1-y2|) */ 561 CV_DIST_L12 =4, /**< L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) */ 562 CV_DIST_FAIR =5, /**< distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 */ 563 CV_DIST_WELSCH =6, /**< distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 */ 564 CV_DIST_HUBER =7 /**< distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345 */ 565 }; 566 567 568 /** Threshold types */ 569 enum 570 { 571 CV_THRESH_BINARY =0, /**< value = value > threshold ? max_value : 0 */ 572 CV_THRESH_BINARY_INV =1, /**< value = value > threshold ? 0 : max_value */ 573 CV_THRESH_TRUNC =2, /**< value = value > threshold ? threshold : value */ 574 CV_THRESH_TOZERO =3, /**< value = value > threshold ? value : 0 */ 575 CV_THRESH_TOZERO_INV =4, /**< value = value > threshold ? 0 : value */ 576 CV_THRESH_MASK =7, 577 CV_THRESH_OTSU =8, /**< use Otsu algorithm to choose the optimal threshold value; 578 combine the flag with one of the above CV_THRESH_* values */ 579 CV_THRESH_TRIANGLE =16 /**< use Triangle algorithm to choose the optimal threshold value; 580 combine the flag with one of the above CV_THRESH_* values, but not 581 with CV_THRESH_OTSU */ 582 }; 583 584 /** Adaptive threshold methods */ 585 enum 586 { 587 CV_ADAPTIVE_THRESH_MEAN_C =0, 588 CV_ADAPTIVE_THRESH_GAUSSIAN_C =1 589 }; 590 591 /** FloodFill flags */ 592 enum 593 { 594 CV_FLOODFILL_FIXED_RANGE =(1 << 16), 595 CV_FLOODFILL_MASK_ONLY =(1 << 17) 596 }; 597 598 599 /** Canny edge detector flags */ 600 enum 601 { 602 CV_CANNY_L2_GRADIENT =(1 << 31) 603 }; 604 605 /** Variants of a Hough transform */ 606 enum 607 { 608 CV_HOUGH_STANDARD =0, 609 CV_HOUGH_PROBABILISTIC =1, 610 CV_HOUGH_MULTI_SCALE =2, 611 CV_HOUGH_GRADIENT =3 612 }; 613 614 615 /* Fast search data structures */ 616 struct CvFeatureTree; 617 struct CvLSH; 618 struct CvLSHOperations; 619 620 /** @} */ 621 622 #ifdef __cplusplus 623 } 624 #endif 625 626 #endif 627