doc/opencv_cheatsheet.tex

   1 %
   2 %    The OpenCV cheatsheet structure:
   3 %
   4 %    opencv data structures
   5 %        point, rect
   6 %        matrix
   7 %
   8 %    creating matrices
   9 %        from scratch
  10 %        from previously allocated data: plain arrays, vectors
  11 %        converting to/from old-style structures
  12 %
  13 %    element access, iteration through matrix elements
  14 %
  15 %    copying & shuffling matrix data
  16 %        copying & converting the whole matrices
  17 %        extracting matrix parts & copying them
  18 %        split, merge & mixchannels
  19 %        flip, transpose, repeat
  20 %
  21 %    matrix & image operations:
  22 %        arithmetics & logic
  23 %        matrix multiplication, inversion, determinant, trace, SVD
  24 %        statistical functions
  25 %
  26 %    basic image processing:
  27 %        image filtering with predefined & custom filters
  28 %        example: finding local maxima
  29 %        geometrical transformations, resize, warpaffine, perspective & remap.
  30 %        color space transformations
  31 %        histograms & back projections
  32 %        contours
  33 %
  34 %    i/o:
  35 %        displaying images
  36 %        saving/loading to/from file (XML/YAML & image file formats)
  37 %        reading videos & camera feed, writing videos
  38 %
  39 %    operations on point sets:
  40 %        findcontours, bounding box, convex hull, min area rect,
  41 %            transformations, to/from homogeneous coordinates
  42 %        matching point sets: homography, fundamental matrix, rigid transforms
  43 %
  44 %    3d:
  45 %        camera calibration, pose estimation.
  46 %        uncalibrated case
  47 %        stereo: rectification, running stereo correspondence, obtaining the depth.
  48 %
  49 %    feature detection:
  50 %        features2d toolbox
  51 %
  52 %    object detection:
  53 %        using a classifier running on a sliding window: cascadeclassifier + hog.
  54 %        using salient point features: features2d -> matching
  55 %
  56 %    statistical data processing:
  57 %        clustering (k-means),
  58 %        classification + regression (SVM, boosting, k-nearest),
  59 %        compressing data (PCA)
  60 %
  61
  62 \documentclass[10pt,landscape]{article}
  63 \usepackage[usenames,dvips,pdftex]{color}
  64 \usepackage{multicol}
  65 \usepackage{calc}
  66 \usepackage{ifthen}
  67 \usepackage[pdftex]{color,graphicx}
  68 \usepackage[landscape]{geometry}
  69 \usepackage{hyperref}
  70 \usepackage[T1]{fontenc}
  71 \hypersetup{colorlinks=true, filecolor=black, linkcolor=black, urlcolor=blue, citecolor=black}
  72 \graphicspath{{./images/}}
  73
  74 % This sets page margins to .5 inch if using letter paper, and to 1cm
  75 % if using A4 paper. (This probably isn't strictly necessary.)
  76 % If using another size paper, use default 1cm margins.
  77 \ifthenelse{\lengthtest { \paperwidth = 11in}}
  78     { \geometry{top=.5in,left=.5in,right=.5in,bottom=.5in} }
  79     {\ifthenelse{ \lengthtest{ \paperwidth = 297mm}}
  80         {\geometry{top=1cm,left=1cm,right=1cm,bottom=1cm} }
  81         {\geometry{top=1cm,left=1cm,right=1cm,bottom=1cm} }
  82     }
  83
  84 % Turn off header and footer
  85 % \pagestyle{empty}
  86
  87 % Redefine section commands to use less space
  88 \makeatletter
  89 \renewcommand{\section}{\@startsection{section}{1}{0mm}%
  90                                 {-1ex plus -.5ex minus -.2ex}%
  91                                 {0.5ex plus .2ex}%x
  92                                 {\normalfont\large\bfseries}}
  93 \renewcommand{\subsection}{\@startsection{subsection}{2}{0mm}%
  94                                 {-1explus -.5ex minus -.2ex}%
  95                                 {0.5ex plus .2ex}%
  96                                 {\normalfont\normalsize\bfseries}}
  97 \renewcommand{\subsubsection}{\@startsection{subsubsection}{3}{0mm}%
  98                                 {-1ex plus -.5ex minus -.2ex}%
  99                                 {1ex plus .2ex}%
 100                                 {\normalfont\small\bfseries}}
 101 \makeatother
 102
 103 % Define BibTeX command
 104 \def\BibTeX{{\rm B\kern-.05em{\sc i\kern-.025em b}\kern-.08em
 105     T\kern-.1667em\lower.7ex\hbox{E}\kern-.125emX}}
 106
 107 % Don't print section numbers
 108 \setcounter{secnumdepth}{0}
 109
 110
 111 %\setlength{\parindent}{0pt}
 112 %\setlength{\parskip}{0pt plus 0.5ex}
 113
 114 \newcommand{\ccode}[1]{
 115 \begin{alltt}
 116 #1
 117 \end{alltt}
 118 }
 119
 120 % -----------------------------------------------------------------------
 121
 122 \begin{document}
 123
 124 \raggedright
 125 \footnotesize
 126 \begin{multicols}{3}
 127
 128
 129 % multicol parameters
 130 % These lengths are set only within the two main columns
 131 %\setlength{\columnseprule}{0.25pt}
 132 \setlength{\premulticols}{1pt}
 133 \setlength{\postmulticols}{1pt}
 134 \setlength{\multicolsep}{1pt}
 135 \setlength{\columnsep}{2pt}
 136
 137 \begin{center}
 138      \Large{\textbf{OpenCV 2.4 Cheat Sheet (C++)}} \\
 139 \end{center}
 140 \newlength{\MyLen}
 141 \settowidth{\MyLen}{\texttt{letterpaper}/\texttt{a4paper} \ }
 142
 143 %\section{Filesystem Concepts}
 144 %\begin{tabular}{@{}p{\the\MyLen}%
 145  %               @{}p{\linewidth-\the\MyLen}@{}}
 146 %\texttt{\href{http://www.ros.org/wiki/Packages}{package}}   & The lowest level of ROS software organization. \\
 147 %\texttt{\href{http://www.ros.org/wiki/Manifest}{manifest}}  & Description of a ROS package. \\
 148 %\texttt{\href{http://www.ros.org/wiki/Stack}{stack}} & Collections of ROS packages that form a higher-level library. \\
 149 %\texttt{\href{http://www.ros.org/wiki/Stack Manifest}{stack manifest}}  & Description of a ROS stack.
 150 %\end{tabular}
 151
 152 \emph{The OpenCV C++ reference manual is here: \url{http://docs.opencv.org}. Use \textbf{Quick Search} to find descriptions of the particular functions and classes}
 153
 154 \section{Key OpenCV Classes}
 155 \begin{tabular}{@{}p{\the\MyLen}%
 156                 @{}p{\linewidth-\the\MyLen}@{}}
 157 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Point_}{Point\_}} & Template 2D point class \\
 158 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Point3_}{Point3\_}} & Template 3D point class \\
 159 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Size_}{Size\_}} & Template size (width, height) class \\
 160 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Vec}{Vec}} & Template short vector class \\
 161 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Matx}{Matx}} & Template small matrix class \\
 162 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Scalar_}{Scalar}} & 4-element vector \\
 163 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Rect_}{Rect}} & Rectangle \\
 164 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Range}{Range}} & Integer value range \\
 165 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Mat}{Mat}} & 2D or multi-dimensional dense array (can be used to store matrices, images, histograms, feature descriptors, voxel volumes etc.)\\
 166 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#sparsemat}{SparseMat}} & Multi-dimensional sparse array \\
 167 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Ptr}{Ptr}} & Template smart pointer class
 168 \end{tabular}
 169
 170 \section{Matrix Basics}
 171 \begin{tabbing}
 172
 173 \textbf{Cr}\=\textbf{ea}\=\textbf{te}\={} \textbf{a matrix} \\
 174 \> \texttt{Mat image(240, 320, CV\_8UC3);} \\
 175
 176 \textbf{[Re]allocate a pre-declared matrix}\\
 177 \> \texttt{image.\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-create}{create}(480, 640, CV\_8UC3);}\\
 178
 179 \textbf{Create a matrix initialized with a constant}\\
 180 \> \texttt{Mat A33(3, 3, CV\_32F, Scalar(5));} \\
 181 \> \texttt{Mat B33(3, 3, CV\_32F); B33 = Scalar(5);} \\
 182 \> \texttt{Mat C33 = Mat::ones(3, 3, CV\_32F)*5.;} \\
 183 \> \texttt{Mat D33 = Mat::zeros(3, 3, CV\_32F) + 5.;} \\
 184
 185 \textbf{Create a matrix initialized with specified values}\\
 186 \> \texttt{double a = CV\_PI/3;} \\
 187 \> \texttt{Mat A22 = (Mat\_<float>(2, 2) <<} \\
 188 \> \> \texttt{cos(a), -sin(a), sin(a), cos(a));} \\
 189 \> \texttt{float B22data[] = \{cos(a), -sin(a), sin(a), cos(a)\};} \\
 190 \> \texttt{Mat B22 = Mat(2, 2, CV\_32F, B22data).clone();}\\
 191
 192 \textbf{Initialize a random matrix}\\
 193 \> \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#randu}{randu}(image, Scalar(0), Scalar(256)); }\textit{// uniform dist}\\
 194 \> \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#randn}{randn}(image, Scalar(128), Scalar(10)); }\textit{// Gaussian dist}\\
 195
 196 \textbf{Convert matrix to/from other structures}\\
 197 \>\textbf{(without copying the data)}\\
 198 \> \texttt{Mat image\_alias = image;}\\
 199 \> \texttt{float* Idata=new float[480*640*3];}\\
 200 \> \texttt{Mat I(480, 640, CV\_32FC3, Idata);}\\
 201 \> \texttt{vector<Point> iptvec(10);}\\
 202 \> \texttt{Mat iP(iptvec); }\textit{// iP -- 10x1 CV\_32SC2 matrix}\\
 203 \> \texttt{IplImage* oldC0 = cvCreateImage(cvSize(320,240),16,1);}\\
 204 \> \texttt{Mat newC = cvarrToMat(oldC0);}\\
 205 \> \texttt{IplImage oldC1 = newC; CvMat oldC2 = newC;}\\
 206
 207 \textbf{... (with copying the data)}\\
 208 \> \texttt{Mat newC2 = cvarrToMat(oldC0).clone();}\\
 209 \> \texttt{vector<Point2f> ptvec = Mat\_<Point2f>(iP);}\\
 210
 211 \>\\
 212 \textbf{Access matrix elements}\\
 213 \> \texttt{A33.at<float>(i,j) = A33.at<float>(j,i)+1;}\\
 214 \> \texttt{Mat dyImage(image.size(), image.type());}\\
 215 \> \texttt{for(int y = 1; y < image.rows-1; y++) \{}\\
 216 \> \> \texttt{Vec3b* prevRow = image.ptr<Vec3b>(y-1);}\\
 217 \> \> \texttt{Vec3b* nextRow = image.ptr<Vec3b>(y+1);}\\
 218 \> \> \texttt{for(int x = 0; x < image.cols; x++)}\\
 219 \> \> \> \texttt{for(int c = 0; c < 3; c++)}\\
 220 \> \> \> \texttt{  dyImage.at<Vec3b>(y,x)[c] =}\\
 221 \> \> \> \texttt{    saturate\_cast<uchar>(}\\
 222 \> \> \> \texttt{       nextRow[x][c] - prevRow[x][c]);}\\
 223 \> \texttt{\} }\\
 224 \> \texttt{Mat\_<Vec3b>::iterator it = image.begin<Vec3b>(),}\\
 225 \> \> \texttt{itEnd = image.end<Vec3b>();}\\
 226 \> \texttt{for(; it != itEnd; ++it)}\\
 227 \> \> \texttt{(*it)[1] \textasciicircum{}= 255;}\\
 228
 229 \end{tabbing}
 230
 231 \section{Matrix Manipulations: Copying, Shuffling, Part Access}
 232 \begin{tabular}{@{}p{\the\MyLen}%
 233                 @{}p{\linewidth-\the\MyLen}@{}}
 234 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-copyto}{src.copyTo(dst)}} & Copy matrix to another one \\
 235 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-convertto}{src.convertTo(dst,type,scale,shift)}} & \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ Scale and convert to another datatype \\
 236 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-clone}{m.clone()}} & Make deep copy of a matrix \\
 237 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-reshape}{m.reshape(nch,nrows)}} & Change matrix dimensions and/or number of channels without copying data \\
 238
 239 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-row}{m.row(i)}},
 240 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-col}{m.col(i)}} & Take a matrix row/column \\
 241
 242 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-rowrange}{m.rowRange(Range(i1,i2))}}
 243 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-colrange}{m.colRange(Range(j1,j2))}} & \ \ \ \ \ \ \ Take a matrix row/column span \\
 244
 245 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#mat-diag}{m.diag(i)}} & Take a matrix diagonal \\
 246
 247 \texttt{\href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#Mat}{m(Range(i1,i2),Range(j1,j2)), m(roi)}} & \ \ \ \ \ \ \ \ \ \ \ \ \ Take a submatrix \\
 248
 249 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#repeat}{m.repeat(ny,nx)}} & Make a bigger matrix from a smaller one \\
 250
 251 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#flip}{flip(src,dst,dir)}} & Reverse the order of matrix rows and/or columns \\
 252
 253 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#split}{split(...)}} & Split multi-channel matrix into separate channels \\
 254
 255 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#merge}{merge(...)}} & Make a multi-channel matrix out of the separate channels \\
 256
 257 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#mixchannels}{mixChannels(...)}} & Generalized form of split() and merge() \\
 258
 259 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#randshuffle}{randShuffle(...)}} & Randomly shuffle matrix elements \\
 260
 261 \end{tabular}
 262
 263 \begin{tabbing}
 264 Exa\=mple 1. Smooth image ROI in-place\\
 265 \>\texttt{Mat imgroi = image(Rect(10, 20, 100, 100));}\\
 266 \>\texttt{GaussianBlur(imgroi, imgroi, Size(5, 5), 1.2, 1.2);}\\
 267 Example 2. Somewhere in a linear algebra algorithm \\
 268 \>\texttt{m.row(i) += m.row(j)*alpha;}\\
 269 Example 3. Copy image ROI to another image with conversion\\
 270 \>\texttt{Rect r(1, 1, 10, 20);}\\
 271 \>\texttt{Mat dstroi = dst(Rect(0,10,r.width,r.height));}\\
 272 \>\texttt{src(r).convertTo(dstroi, dstroi.type(), 1, 0);}\\
 273 \end{tabbing}
 274
 275 \section{Simple Matrix Operations}
 276
 277 OpenCV implements most common arithmetical, logical and
 278 other matrix operations, such as
 279
 280 \begin{itemize}
 281 \item
 282 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#add}{add()}},
 283 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#subtract}{subtract()}},
 284 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#multiply}{multiply()}},
 285 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#divide}{divide()}},
 286 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#absdiff}{absdiff()}},
 287 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#bitwise-and}{bitwise\_and()}},
 288 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#bitwise-or}{bitwise\_or()}},
 289 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#bitwise-xor}{bitwise\_xor()}},
 290 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#max}{max()}},
 291 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#min}{min()}},
 292 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#compare}{compare()}}
 293
 294 -- correspondingly, addition, subtraction, element-wise multiplication ... comparison of two matrices or a matrix and a scalar.
 295
 296 \begin{tabbing}
 297 Exa\=mple. \href{http://en.wikipedia.org/wiki/Alpha_compositing}{Alpha compositing} function:\\
 298 \texttt{void alphaCompose(const Mat\& rgba1,}\\
 299 \> \texttt{const Mat\& rgba2, Mat\& rgba\_dest)}\\
 300 \texttt{\{ }\\
 301 \> \texttt{Mat a1(rgba1.size(), rgba1.type()), ra1;}\\
 302 \> \texttt{Mat a2(rgba2.size(), rgba2.type());}\\
 303 \> \texttt{int mixch[]=\{3, 0, 3, 1, 3, 2, 3, 3\};}\\
 304 \> \texttt{mixChannels(\&rgba1, 1, \&a1, 1, mixch, 4);}\\
 305 \> \texttt{mixChannels(\&rgba2, 1, \&a2, 1, mixch, 4);}\\
 306 \> \texttt{subtract(Scalar::all(255), a1, ra1);}\\
 307 \> \texttt{bitwise\_or(a1, Scalar(0,0,0,255), a1);}\\
 308 \> \texttt{bitwise\_or(a2, Scalar(0,0,0,255), a2);}\\
 309 \> \texttt{multiply(a2, ra1, a2, 1./255);}\\
 310 \> \texttt{multiply(a1, rgba1, a1, 1./255);}\\
 311 \> \texttt{multiply(a2, rgba2, a2, 1./255);}\\
 312 \> \texttt{add(a1, a2, rgba\_dest);}\\
 313 \texttt{\}}
 314 \end{tabbing}
 315
 316 \item
 317
 318 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#sum}{sum()}},
 319 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#mean}{mean()}},
 320 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#meanstddev}{meanStdDev()}},
 321 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#norm}{norm()}},
 322 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#countnonzero}{countNonZero()}},
 323 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#minmaxloc}{minMaxLoc()}},
 324
 325 -- various statistics of matrix elements.
 326
 327 \item
 328 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#exp}{exp()}},
 329 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#log}{log()}},
 330 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#pow}{pow()}},
 331 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#sqrt}{sqrt()}},
 332 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#carttopolar}{cartToPolar()}},
 333 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#polartocart}{polarToCart()}}
 334
 335 -- the classical math functions.
 336
 337 \item
 338 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#scaleadd}{scaleAdd()}},
 339 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#transpose}{transpose()}},
 340 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#gemm}{gemm()}},
 341 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#invert}{invert()}},
 342 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#solve}{solve()}},
 343 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#determinant}{determinant()}},
 344 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#trace}{trace()}},
 345 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#eigen}{eigen()}},
 346 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#SVD}{SVD}},
 347
 348 -- the algebraic functions + SVD class.
 349
 350 \item
 351 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#dft}{dft()}},
 352 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#idft}{idft()}},
 353 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#dct}{dct()}},
 354 \texttt{\href{http://docs.opencv.org/modules/core/doc/operations_on_arrays.html\#idct}{idct()}},
 355
 356 -- discrete Fourier and cosine transformations
 357
 358 \end{itemize}
 359
 360 For some operations a more convenient \href{http://docs.opencv.org/modules/core/doc/basic_structures.html\#matrix-expressions}{algebraic notation} can be used, for example:
 361 \begin{tabbing}
 362 \texttt{Mat}\={} \texttt{delta = (J.t()*J + lambda*}\\
 363 \>\texttt{Mat::eye(J.cols, J.cols, J.type()))}\\
 364 \>\texttt{.inv(CV\_SVD)*(J.t()*err);}
 365 \end{tabbing}
 366 implements the core of Levenberg-Marquardt optimization algorithm.
 367
 368 \section{Image Processsing}
 369
 370 \subsection{Filtering}
 371
 372 \begin{tabular}{@{}p{\the\MyLen}%
 373                 @{}p{\linewidth-\the\MyLen}@{}}
 374 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#filter2d}{filter2D()}} & Non-separable linear filter \\
 375
 376 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#sepfilter2d}{sepFilter2D()}} & Separable linear filter \\
 377
 378 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#blur}{boxFilter()}},  \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#gaussianblur}{GaussianBlur()}},
 379 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#medianblur}{medianBlur()}},
 380 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#bilateralfilter}{bilateralFilter()}}
 381 & Smooth the image with one of the linear or non-linear filters \\
 382
 383 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#sobel}{Sobel()}},  \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#scharr}{Scharr()}}
 384 & Compute the spatial image derivatives \\
 385 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#laplacian}{Laplacian()}} & compute Laplacian: $\Delta I = \frac{\partial ^ 2 I}{\partial x^2} + \frac{\partial ^ 2 I}{\partial y^2}$  \\
 386
 387 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#erode}{erode()}}, \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/filtering.html\#dilate}{dilate()}} & Morphological operations \\
 388
 389 \end{tabular}
 390
 391 \begin{tabbing}
 392 Exa\=mple. Filter image in-place with a 3x3 high-pass kernel\\
 393 \> (preserve negative responses by shifting the result by 128):\\
 394 \texttt{filter2D(image, image, image.depth(), (Mat\_<float>(3,3)<<}\\
 395 \> \texttt{-1, -1, -1, -1, 9, -1, -1, -1, -1), Point(1,1), 128);}\\
 396 \end{tabbing}
 397
 398 \subsection{Geometrical Transformations}
 399
 400 \begin{tabular}{@{}p{\the\MyLen}%
 401                 @{}p{\linewidth-\the\MyLen}@{}}
 402 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#resize}{resize()}} & Resize image \\
 403
 404 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#getrectsubpix}{getRectSubPix()}} & Extract an image patch \\
 405
 406 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#warpaffine}{warpAffine()}} & Warp image affinely\\
 407
 408 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#warpperspective}{warpPerspective()}} & Warp image perspectively\\
 409
 410 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#remap}{remap()}} & Generic image warping\\
 411
 412 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#convertmaps}{convertMaps()}} & Optimize maps for a faster remap() execution\\
 413
 414 \end{tabular}
 415
 416 \begin{tabbing}
 417 Example. Decimate image by factor of $\sqrt{2}$:\\
 418 \texttt{Mat dst; resize(src, dst, Size(), 1./sqrt(2), 1./sqrt(2));}
 419 \end{tabbing}
 420
 421 \subsection{Various Image Transformations}
 422
 423 \begin{tabular}{@{}p{\the\MyLen}%
 424                 @{}p{\linewidth-\the\MyLen}@{}}
 425
 426 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#cvtcolor}{cvtColor()}} & Convert image from one color space to another \\
 427
 428 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#threshold}{threshold()}}, \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#adaptivethreshold}{adaptivethreshold()}} & Convert grayscale image to binary image using a fixed or a variable threshold \\
 429
 430 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#floodfill}{floodFill()}} & Find a connected component using region growing algorithm\\
 431
 432 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#integral}{integral()}} & Compute integral image \\
 433
 434 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#distancetransform}{distanceTransform()}}
 435  & build distance map or discrete Voronoi diagram for a binary image. \\
 436
 437 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#watershed}{watershed()}},
 438 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html\#grabcut}{grabCut()}}
 439  & marker-based image segmentation algorithms.
 440  See the samples \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/watershed.cpp}{watershed.cpp}} and \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/grabcut.cpp}{grabcut.cpp}}.
 441
 442 \end{tabular}
 443
 444 \subsection{Histograms}
 445
 446 \begin{tabular}{@{}p{\the\MyLen}%
 447                 @{}p{\linewidth-\the\MyLen}@{}}
 448
 449 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/histograms.html\#calchist}{calcHist()}} & Compute image(s) histogram \\
 450
 451 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/histograms.html\#calcbackproject}{calcBackProject()}} & Back-project the histogram \\
 452
 453 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/histograms.html\#equalizehist}{equalizeHist()}} & Normalize image brightness and contrast\\
 454
 455 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/histograms.html\#comparehist}{compareHist()}} & Compare two histograms\\
 456
 457 \end{tabular}
 458
 459 \begin{tabbing}
 460 Example. Compute Hue-Saturation histogram of an image:\\
 461 \texttt{Mat hsv, H;}\\
 462 \texttt{cvtColor(image, hsv, CV\_BGR2HSV);}\\
 463 \texttt{int planes[]=\{0, 1\}, hsize[] = \{32, 32\};}\\
 464 \texttt{calcHist(\&hsv, 1, planes, Mat(), H, 2, hsize, 0);}\\
 465 \end{tabbing}
 466
 467 \subsection{Contours}
 468 See \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/contours2.cpp}{contours2.cpp}} and \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/squares.cpp}{squares.cpp}}
 469 samples on what are the contours and how to use them.
 470
 471 \section{Data I/O}
 472
 473 \href{http://docs.opencv.org/modules/core/doc/xml_yaml_persistence.html\#xml-yaml-file-storages-writing-to-a-file-storage}{XML/YAML storages} are collections (possibly nested) of scalar values, structures and heterogeneous lists.
 474
 475 \begin{tabbing}
 476 \textbf{Wr}\=\textbf{iting data to YAML (or XML)}\\
 477 \texttt{// Type of the file is determined from the extension}\\
 478 \texttt{FileStorage fs("test.yml", FileStorage::WRITE);}\\
 479 \texttt{fs << "i" << 5 << "r" << 3.1 << "str" << "ABCDEFGH";}\\
 480 \texttt{fs << "mtx" << Mat::eye(3,3,CV\_32F);}\\
 481 \texttt{fs << "mylist" << "[" << CV\_PI << "1+1" <<}\\
 482 \>\texttt{"\{:" << "month" << 12 << "day" << 31 << "year"}\\
 483 \>\texttt{<< 1969 << "\}" << "]";}\\
 484 \texttt{fs << "mystruct" << "\{" << "x" << 1 << "y" << 2 <<}\\
 485 \>\texttt{"width" << 100 << "height" << 200 << "lbp" << "[:";}\\
 486 \texttt{const uchar arr[] = \{0, 1, 1, 0, 1, 1, 0, 1\};}\\
 487 \texttt{fs.writeRaw("u", arr, (int)(sizeof(arr)/sizeof(arr[0])));}\\
 488 \texttt{fs << "]" << "\}";}
 489 \end{tabbing}
 490
 491 \emph{Scalars (integers, floating-point numbers, text strings), matrices, STL vectors of scalars and some other types can be written to the file storages using \texttt{<<} operator}
 492
 493 \begin{tabbing}
 494 \textbf{Re}\=\textbf{ading the data back}\\
 495 \texttt{// Type of the file is determined from the content}\\
 496 \texttt{FileStorage fs("test.yml", FileStorage::READ);}\\
 497 \texttt{int i1 = (int)fs["i"]; double r1 = (double)fs["r"];}\\
 498 \texttt{string str1 = (string)fs["str"];}\\
 499
 500 \texttt{Mat M; fs["mtx"] >> M;}\\
 501
 502 \texttt{FileNode tl = fs["mylist"];}\\
 503 \texttt{CV\_Assert(tl.type() == FileNode::SEQ \&\& tl.size() == 3);}\\
 504 \texttt{double tl0 = (double)tl[0]; string tl1 = (string)tl[1];}\\
 505
 506 \texttt{int m = (int)tl[2]["month"], d = (int)tl[2]["day"];}\\
 507 \texttt{int year = (int)tl[2]["year"];}\\
 508
 509 \texttt{FileNode tm = fs["mystruct"];}\\
 510
 511 \texttt{Rect r; r.x = (int)tm["x"], r.y = (int)tm["y"];}\\
 512 \texttt{r.width = (int)tm["width"], r.height = (int)tm["height"];}\\
 513
 514 \texttt{int lbp\_val = 0;}\\
 515 \texttt{FileNodeIterator it = tm["lbp"].begin();}\\
 516
 517 \texttt{for(int k = 0; k < 8; k++, ++it)}\\
 518 \>\texttt{lbp\_val |= ((int)*it) << k;}\\
 519 \end{tabbing}
 520
 521 \emph{Scalars are read using the corresponding FileNode's cast operators. Matrices and some other types are read using \texttt{>>} operator. Lists can be read using FileNodeIterator's.}
 522
 523 \begin{tabbing}
 524 \textbf{Wr}\=\textbf{iting and reading raster images}\\
 525 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html\#imwrite}{imwrite}("myimage.jpg", image);}\\
 526 \texttt{Mat image\_color\_copy = \href{http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html\#imread}{imread}("myimage.jpg", 1);}\\
 527 \texttt{Mat image\_grayscale\_copy = \href{http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html\#imread}{imread}("myimage.jpg", 0);}\\
 528 \end{tabbing}
 529
 530 \emph{The functions can read/write images in the following formats: \textbf{BMP (.bmp), JPEG (.jpg, .jpeg), TIFF (.tif, .tiff), PNG (.png), PBM/PGM/PPM (.p?m), Sun Raster (.sr), JPEG 2000 (.jp2)}. Every format supports 8-bit, 1- or 3-channel images. Some formats (PNG, JPEG 2000) support 16 bits per channel.}
 531
 532 \begin{tabbing}
 533 \textbf{Re}\=\textbf{ading video from a file or from a camera}\\
 534 \texttt{VideoCapture cap;}\\
 535 \texttt{if(argc > 1) cap.open(string(argv[1])); else cap.open(0)};\\
 536 \texttt{Mat frame; namedWindow("video", 1);}\\
 537 \texttt{for(;;) \{}\\
 538 \>\texttt{cap >> frame; if(!frame.data) break;}\\
 539 \>\texttt{imshow("video", frame); if(waitKey(30) >= 0) break;}\\
 540 \texttt{\} }
 541 \end{tabbing}
 542
 543 \section{Simple GUI (highgui module)}
 544
 545 \begin{tabular}{@{}p{\the\MyLen}%
 546                 @{}p{\linewidth-\the\MyLen}@{}}
 547
 548 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/user_interface.html\#namedwindow}{namedWindow(winname,flags)}} & \ \ \ \ \ \ \ \ \ \ Create named highgui window \\
 549
 550 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/user_interface.html\#destroywindow}{destroyWindow(winname)}} & \ \ \ Destroy the specified window \\
 551
 552 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/user_interface.html\#imshow}{imshow(winname, mtx)}} & Show image in the window \\
 553
 554 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/user_interface.html\#waitkey}{waitKey(delay)}} & Wait for a key press during the specified time interval (or forever). Process events while waiting. \emph{Do not forget to call this function several times a second in your code.} \\
 555
 556 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/user_interface.html\#createtrackbar}{createTrackbar(...)}} & Add trackbar (slider) to the specified window \\
 557
 558 \texttt{\href{http://docs.opencv.org/modules/highgui/doc/user_interface.html\#setmousecallback}{setMouseCallback(...)}} & \ \ Set the callback on mouse clicks and movements in the specified window \\
 559
 560 \end{tabular}
 561
 562 See \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/camshiftdemo.cpp}{camshiftdemo.cpp}} and other \href{https://github.com/Itseez/opencv/tree/master/samples/}{OpenCV samples} on how to use the GUI functions.
 563
 564 \section{Camera Calibration, Pose Estimation and Depth Estimation}
 565
 566 \begin{tabular}{@{}p{\the\MyLen}%
 567                 @{}p{\linewidth-\the\MyLen}@{}}
 568
 569 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#calibratecamera}{calibrateCamera()}} & Calibrate camera from several views of a calibration pattern. \\
 570
 571 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#findchessboardcorners}{findChessboardCorners()}} & \ \ \ \ \ \ Find feature points on the checkerboard calibration pattern. \\
 572
 573 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#solvepnp}{solvePnP()}} & Find the object pose from the known projections of its feature points. \\
 574
 575 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#stereocalibrate}{stereoCalibrate()}} & Calibrate stereo camera. \\
 576
 577 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#stereorectify}{stereoRectify()}} & Compute the rectification transforms for a calibrated stereo camera.\\
 578
 579 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html\#initundistortrectifymap}{initUndistortRectifyMap()}} & \ \ \ \ \ \ Compute rectification map (for \texttt{remap()}) for each stereo camera head.\\
 580
 581 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#StereoBM}{StereoBM}}, \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#StereoSGBM}{StereoSGBM}} & The stereo correspondence engines to be run on rectified stereo pairs.\\
 582
 583 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#reprojectimageto3d}{reprojectImageTo3D()}} & Convert disparity map to 3D point cloud.\\
 584
 585 \texttt{\href{http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html\#findhomography}{findHomography()}} & Find best-fit perspective transformation between two 2D point sets. \\
 586
 587 \end{tabular}
 588
 589 To calibrate a camera, you can use \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/calibration.cpp}{calibration.cpp}} or
 590 \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/stereo\_calib.cpp}{stereo\_calib.cpp}} samples.
 591 To get the disparity maps and the point clouds, use
 592 \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/stereo\_match.cpp}{stereo\_match.cpp}} sample.
 593
 594 \section{Object Detection}
 595
 596 \begin{tabular}{@{}p{\the\MyLen}%
 597                 @{}p{\linewidth-\the\MyLen}@{}}
 598                 \texttt{\href{http://docs.opencv.org/modules/imgproc/doc/object_detection.html\#matchtemplate}{matchTemplate}} & Compute proximity map for given template.\\
 599
 600 \texttt{\href{http://docs.opencv.org/modules/objdetect/doc/cascade_classification.html\#cascadeclassifier}{CascadeClassifier}} & Viola's Cascade of Boosted classifiers using Haar or LBP features. Suits for detecting faces, facial features and some other objects without diverse textures. See \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/c/facedetect.cpp}{facedetect.cpp}}\\
 601
 602 \texttt{{HOGDescriptor}} & N. Dalal's object detector using Histogram-of-Oriented-Gradients (HOG) features. Suits for detecting people, cars and other objects with well-defined silhouettes. See \texttt{\href{https://github.com/Itseez/opencv/tree/master/samples/cpp/peopledetect.cpp}{peopledetect.cpp}}\\
 603
 604 \end{tabular}
 605
 606 %
 607 %    feature detection:
 608 %        features2d toolbox
 609 %
 610 %    object detection:
 611 %        using a classifier running on a sliding window: cascadeclassifier + hog.
 612 %        using salient point features: features2d -> matching
 613 %
 614 %    statistical data processing:
 615 %        clustering (k-means),
 616 %        classification + regression (SVM, boosting, k-nearest),
 617 %        compressing data (PCA)
 618
 619 \end{multicols}
 620 \end{document}