Merge pull request #181 from samyak-268:master

pull/471/head
Vadim Pisarevsky 9 years ago
commit b891ce2c2c
  1. 9
      modules/ximgproc/include/opencv2/ximgproc.hpp
  2. 58
      modules/ximgproc/samples/niblack_thresholding.cpp
  3. 100
      modules/ximgproc/src/niblack_thresholding.cpp

@ -63,4 +63,13 @@ which somehow takes into account pixel affinities in natural images.
@}
*/
namespace cv {
namespace ximgproc {
CV_EXPORTS_W
void niBlackThreshold( InputArray _src, OutputArray _dst, double maxValue,
int type, int blockSize, double delta );
} // namespace ximgproc
} //namespace cv
#endif

@ -0,0 +1,58 @@
/*
* Sample C++ to demonstrate Niblack thresholding.
*
*/
#include <iostream>
#include <cstdio>
#include "opencv2/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/ximgproc.hpp"
using namespace std;
using namespace cv;
using namespace cv::ximgproc;
Mat_<uchar> src, dst;
const int k_max_value = 10;
int k_from_slider = 0;
double k_actual = 0.0;
void on_trackbar(int, void*);
int main(int argc, char** argv)
{
/*
* Read filename from the command-line and load
* corresponding gray-scale image.
*/
if(argc != 2)
{
cout << "Usage: ./niblack_thresholding [IMAGE]\n";
return 1;
}
const char* filename = argv[1];
src = imread(filename, 1);
namedWindow("k-slider", 1);
string trackbar_name = "k";
createTrackbar(trackbar_name, "k-slider", &k_from_slider, k_max_value, on_trackbar);
on_trackbar(k_from_slider, 0);
imshow("Source", src);
waitKey(0);
return 0;
}
void on_trackbar(int, void*)
{
k_actual = (double)k_from_slider/k_max_value;
niBlackThreshold(src, dst, 255, THRESH_BINARY, 3, k_actual);
imshow("Destination", dst);
}

@ -0,0 +1,100 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, Beat Kueng (beat-kueng@gmx.net), Lukas Vogel, Morten Lysgaard
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <cmath>
namespace cv {
namespace ximgproc {
void niBlackThreshold( InputArray _src, OutputArray _dst, double maxValue,
int type, int blockSize, double delta )
{
Mat src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 );
CV_Assert( blockSize % 2 == 1 && blockSize > 1 );
Size size = src.size();
_dst.create( size, src.type() );
Mat dst = _dst.getMat();
if( maxValue < 0 )
{
dst = Scalar(0);
return;
}
// Calculate and store the mean and mean of squares in the neighborhood
// of each pixel and store them in Mat mean and sqmean.
Mat_<float> mean(size), sqmean(size);
if( src.data != dst.data )
mean = dst;
boxFilter( src, mean, CV_64F, Size(blockSize, blockSize),
Point(-1,-1), true, BORDER_REPLICATE );
sqrBoxFilter( src, sqmean, CV_64F, Size(blockSize, blockSize),
Point(-1,-1), true, BORDER_REPLICATE );
// Compute (k * standard deviation) in the neighborhood of each pixel
// and store in Mat stddev. Also threshold the values in the src matrix to compute dst matrix.
Mat_<float> stddev(size);
int i, j, threshold;
uchar imaxval = saturate_cast<uchar>(maxValue);
for(i = 0; i < size.height; ++i)
{
for(j = 0; j < size.width; ++j)
{
stddev.at<float>(i, j) = saturate_cast<float>(delta) * cvRound( sqrt(sqmean.at<float>(i, j) -
mean.at<float>(i, j)*mean.at<float>(i, j)) );
threshold = cvRound(mean.at<float>(i, j) + stddev.at<float>(i, j));
if(src.at<uchar>(i, j) > threshold)
dst.at<uchar>(i, j) = (type == THRESH_BINARY) ? imaxval : 0;
else
dst.at<uchar>(i, j) = (type == THRESH_BINARY) ? 0 : imaxval;
}
}
}
} // namespace ximgproc
} //namespace cv
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