From 8877e3aedb1a21230ff1db99cf2463cc7f662a65 Mon Sep 17 00:00:00 2001 From: saskatchewancatch Date: Fri, 8 Sep 2017 19:55:19 -0600 Subject: [PATCH] Adjustmenbts --- modules/core/include/opencv2/core.hpp | 32 ++++---------------------------- 1 file changed, 4 insertions(+), 28 deletions(-) diff --git a/modules/core/include/opencv2/core.hpp b/modules/core/include/opencv2/core.hpp index 5c56d17..8561401 100644 --- a/modules/core/include/opencv2/core.hpp +++ b/modules/core/include/opencv2/core.hpp @@ -644,20 +644,6 @@ CV_EXPORTS_W void meanStdDev(InputArray src, OutputArray mean, OutputArray stdde This version of cv::norm calculates the absolute norm of src1. The type of norm to calculate is specified using cv::NormTypes. -If normType is not specified, NORM_L2 is used. - ---done edit-- - -\f[norm = \forkfour{\|\texttt{src1}\|_{L_{\infty}} = \max _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) } -{ \| \texttt{src1} \| _{L_1} = \sum _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) } -{ \| \texttt{src1} \| _{L_2} = \sqrt{\sum_I \texttt{src1}(I)^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) } -{ \| \texttt{src1} \| _{L_2} ^{2} = \sum_I \texttt{src1}(I)^2} {if \(\texttt{normType} = \texttt{NORM_L2SQR}\)}\f] - -If normType is not specified, NORM_L2 is used. - -or an absolute or relative difference norm if src2 is there: - - As example for one array consider the function \f$r(x)= \begin{pmatrix} x \\ 1-x \end{pmatrix}, x \in [-1;1]\f$. The \f$ L_{1}, L_{2} \f$ and \f$ L_{\infty} \f$ norm for the sample value \f$r(-1) = \begin{pmatrix} -1 \\ 2 \end{pmatrix}\f$ is calculated as follows @@ -676,14 +662,16 @@ The following graphic shows all values for the three norm functions \f$\| r(x) \ It is notable that the \f$ L_{1} \f$ norm forms the upper and the \f$ L_{\infty} \f$ norm forms the lower border for the example function \f$ r(x) \f$. ![Graphs for the different norm functions from the above example](pics/NormTypes_OneArray_1-2-INF.png) -The function cv::norm returns the calculated norm. - When the mask parameter is specified and it is not empty, the norm is + +If normType is not specified, NORM_L2 is used. calculated only over the region specified by the mask. Multi-channel input arrays are treated as single-channel arrays, that is, the results for all channels are combined. +Hamming norms can only be calculated with CV_8U depth arrays. + @param src1 first input array. @param normType type of the norm (see cv::NormTypes). @param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type. @@ -696,18 +684,6 @@ This version of cv::norm calculates the absolute difference norm or the relative difference norm of arrays src1 and src2. The type of norm to calculate is specified using cv::NormTypes. -\f[norm = \forkfour{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} = \max _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) } -{ \| \texttt{src1} - \texttt{src2} \| _{L_1} = \sum _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) } -{ \| \texttt{src1} - \texttt{src2} \| _{L_2} = \sqrt{\sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) } -{ \| \texttt{src1} - \texttt{src2} \| _{L_2} ^{2} = \sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2 }{if \(\texttt{normType} = \texttt{NORM_L2SQR}\) } -\f] - -or - -\f[norm = \forkthree{\frac{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} }{\|\texttt{src2}\|_{L_{\infty}} }}{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_INF}\) } -{ \frac{\|\texttt{src1}-\texttt{src2}\|_{L_1} }{\|\texttt{src2}\|_{L_1}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L1}\) } -{ \frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2}\) }\f] - @param src1 first input array. @param src2 second input array of the same size and the same type as src1. @param normType type of the norm (cv::NormTypes). -- 2.7.4