opencv 2 computer vision application programming第五章翻译

第五章 用生态学过滤方法改变图像

这一章我们讨论：
用形态过滤器磨损和扩大图像
用形态过滤器打开和关闭图像
用形态过滤器做边缘检测和角点检测
用水印分割图像
用抓取切割算法提取前景中物体

 

到google上找到了书对应的代码下载了，然后条码的边缘检测有了点想法。

/*------------------------------------------------------------------------------------------*\
   This file contains material supporting chapter 5 of the cookbook:
   Computer Vision Programming using the OpenCV Library.
   by Robert Laganiere, Packt Publishing, 2011.

   This program is free software; permission is hereby granted to use, copy, modify,
   and distribute this source code, or portions thereof, for any purpose, without fee,
   subject to the restriction that the copyright notice may not be removed
   or altered from any source or altered source distribution.
   The software is released on an as-is basis and without any warranties of any kind.
   In particular, the software is not guaranteed to be fault-tolerant or free from failure.
   The author disclaims all warranties with regard to this software, any use,
   and any consequent failure, is purely the responsibility of the user.

   Copyright (C) 2010-2011 Robert Laganiere, www.laganiere.name
\*------------------------------------------------------------------------------------------*/

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include "morphoFeatures.h"

int main()
{
    // Read input image
    cv::Mat image= cv::imread("C:/testdir/barcode5.jpg",0);
    if (!image.data)
        return 0;

    // Display the image
 //   cv::namedWindow("Image");
    cv::imshow("Image",image);

    // Create the morphological features instance
    MorphoFeatures morpho;
    morpho.setThreshold(40);

    // Get the edges
    cv::Mat edges;
    edges= morpho.getEdges(image);

    // Display the edge image
    cv::namedWindow("Edge Image");
    cv::imshow("Edge Image",edges);

    // Get the corners
    morpho.setThreshold(-1);
    cv::Mat corners;
    corners= morpho.getCorners(image);
    cv::morphologyEx(corners,corners,cv::MORPH_TOPHAT,cv::Mat());
    cv::threshold(corners, corners, 40, 255, cv::THRESH_BINARY_INV);

    // Display the corner image
    cv::namedWindow("Corner Image");
    cv::imshow("Corner Image",corners);

    // Display the corner on the image
    morpho.drawOnImage(corners,image);
    cv::namedWindow("Corners on Image");
    cv::imshow("Corners on Image",image);
/*
    // Read and display image of square
    image= cv::imread("C:/testdir/square.jpg",0);
    cv::namedWindow("Square Image");
    cv::imshow("Square Image",image);

    // Creating the cross-shaped structuring element
    cv::Mat cross(5,5,CV_8U,cv::Scalar(0));
    for (int i=0; i<5; i++) {

      cross.at<uchar>(2,i)= 1;
      cross.at<uchar>(i,2)= 1;
    }

    // Dilate with a cross
    cv::Mat result;
    cv::dilate(image,result,cross);

    // Display the result
    cv::namedWindow("Dilated square with cross");
    cv::imshow("Dilated square with cross",result);

    // Creating the diamond-shaped structuring element
    cv::Mat diamond(5,5,CV_8U,cv::Scalar(1));
    diamond.at<uchar>(0,0)= 0;
    diamond.at<uchar>(0,1)= 0;
    diamond.at<uchar>(1,0)= 0;
    diamond.at<uchar>(4,4)= 0;
    diamond.at<uchar>(3,4)= 0;
    diamond.at<uchar>(4,3)= 0;
    diamond.at<uchar>(4,0)= 0;
    diamond.at<uchar>(4,1)= 0;
    diamond.at<uchar>(3,0)= 0;
    diamond.at<uchar>(0,4)= 0;
    diamond.at<uchar>(0,3)= 0;
    diamond.at<uchar>(1,4)= 0;

    // Erode with a diamond
    cv::Mat result2;
    cv::erode(result,result2,diamond);

    // Display the result
    cv::namedWindow("Eroded square with diamond");
    cv::imshow("Eroded square with diamond",result2);

    // Combine the images into one
    cv::Mat final(100,300,CV_8U);
    cv::Mat window= final(cv::Rect(0,0,100,100));
    image.copyTo(window);
    window= final(cv::Rect(100,0,100,100));
    result.copyTo(window);
    window= final(cv::Rect(200,0,100,100));
    result2.copyTo(window);

    // Display the combined result
    cv::namedWindow("Combined");
    cv::imshow("Combined",final);

    // Save combined result
    cv::imwrite("squares.bmp",final);
*/
    cv::waitKey();

    return 0;
}

 

morphoFeatures.h:

/*------------------------------------------------------------------------------------------*\
   This file contains material supporting chapter 5 of the cookbook:  
   Computer Vision Programming using the OpenCV Library. 
   by Robert Laganiere, Packt Publishing, 2011.

   This program is free software; permission is hereby granted to use, copy, modify, 
   and distribute this source code, or portions thereof, for any purpose, without fee, 
   subject to the restriction that the copyright notice may not be removed 
   or altered from any source or altered source distribution. 
   The software is released on an as-is basis and without any warranties of any kind. 
   In particular, the software is not guaranteed to be fault-tolerant or free from failure. 
   The author disclaims all warranties with regard to this software, any use, 
   and any consequent failure, is purely the responsibility of the user.
 
   Copyright (C) 2010-2011 Robert Laganiere, www.laganiere.name
\*------------------------------------------------------------------------------------------*/

#if !defined MORPHOF
#define MORPHOF

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>

class MorphoFeatures {

  private:

      // threshold to produce binary image
      int threshold;
      // structuring elements used in corner detection
      cv::Mat cross;
      cv::Mat diamond;
      cv::Mat square;
      cv::Mat x;

      void applyThreshold(cv::Mat& result) {

          // Apply threshold on result
          if (threshold>0)
            cv::threshold(result, result, threshold, 255, cv::THRESH_BINARY_INV);
      }

  public:

      MorphoFeatures() : threshold(-1), cross(5,5,CV_8U,cv::Scalar(0)), 
                                        diamond(5,5,CV_8U,cv::Scalar(1)), 
                                        square(5,5,CV_8U,cv::Scalar(1)),
                                        x(5,5,CV_8U,cv::Scalar(0)){
    
          // Creating the cross-shaped structuring element
          for (int i=0; i<5; i++) {
          
              cross.at<uchar>(2,i)= 1;
              cross.at<uchar>(i,2)= 1;                                    
          }
          
          // Creating the diamond-shaped structuring element
          diamond.at<uchar>(0,0)= 0;
          diamond.at<uchar>(0,1)= 0;
          diamond.at<uchar>(1,0)= 0;
          diamond.at<uchar>(4,4)= 0;
          diamond.at<uchar>(3,4)= 0;
          diamond.at<uchar>(4,3)= 0;
          diamond.at<uchar>(4,0)= 0;
          diamond.at<uchar>(4,1)= 0;
          diamond.at<uchar>(3,0)= 0;
          diamond.at<uchar>(0,4)= 0;
          diamond.at<uchar>(0,3)= 0;
          diamond.at<uchar>(1,4)= 0;
          
          // Creating the x-shaped structuring element
          for (int i=0; i<5; i++) {
          
              x.at<uchar>(i,i)= 1;
              x.at<uchar>(4-i,i)= 1;                                    
          }
      }

      void setThreshold(int t) {

          threshold= t;
      }

      int getThreshold() const {

          return threshold;
      }

      cv::Mat getEdges(const cv::Mat &image) {

          // Get the gradient image
          cv::Mat result;
          cv::morphologyEx(image,result,cv::MORPH_GRADIENT,cv::Mat());

          // Apply threshold to obtain a binary image
          applyThreshold(result);

          return result;
      }

      cv::Mat getCorners(const cv::Mat &image) {

          cv::Mat result;

          // Dilate with a cross    
          cv::dilate(image,result,cross);

          // Erode with a diamond
          cv::erode(result,result,diamond);

          cv::Mat result2;
          // Dilate with a X    
          cv::dilate(image,result2,x);

          // Erode with a square
          cv::erode(result2,result2,square);

          // Corners are obtained by differencing
          // the two closed images
          cv::absdiff(result2,result,result);

          // Apply threshold to obtain a binary image
          applyThreshold(result);

          return result;
      }

      void drawOnImage(const cv::Mat& binary, cv::Mat& image) {
                
          cv::Mat_<uchar>::const_iterator it= binary.begin<uchar>();
          cv::Mat_<uchar>::const_iterator itend= binary.end<uchar>();

          // for each pixel    
          for (int i=0; it!= itend; ++it,++i) {
              if (!*it)
                  cv::circle(image,cv::Point(i%image.step,i/image.step),5,cv::Scalar(255,0,0));
          }
      }
};


#endif

 

 

用500万像素的手机拍条码，边缘检测后虽然条码里面很乱但条码边框（黑色）能够确定了。