HSV顏色範圍內的遮罩應用－天天向上

請先參考下面這一篇, 篩選RGB得到顏色範圍內的遮罩

- RGB顏色範圍內的遮罩應用 Part II
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- 先來認識inRange函式定義
- inRange
  Checks if array elements lie between the elements of two other arrays.
  
  C++: void inRange(InputArray src, InputArray lowerb, InputArray upperb, OutputArray dst)
  
  Python: cv2.inRange(src, lowerb, upperb[, dst]) → dst
  
  C: void cvInRange(const CvArr* src, const CvArr* lower, const CvArr* upper, CvArr* dst)
  
  C: void cvInRangeS(const CvArr* src, CvScalar lower, CvScalar upper, CvArr* dst)
  
  Python: cv.InRange(src, lower, upper, dst) → None
  Python: cv.InRangeS(src, lower, upper, dst) → None
  Parameters:
  - src – first input array.
  - lowerb – inclusive lower boundary array or a scalar.
  - upperb – inclusive upper boundary array or a scalar.
  - dst – output array of the same size as src and CV_8U type.
  The function checks the range as follows:
  - For every element of a single-channel input array:
    $\texttt{dst} (I)= \texttt{lowerb} (I)_0 \leq \texttt{src} (I)_0 \leq \texttt{upperb} (I)_0$
  - For two-channel arrays:
    $\texttt{dst} (I)= \texttt{lowerb} (I)_0 \leq \texttt{src} (I)_0 \leq \texttt{upperb} (I)_0 \land \texttt{lowerb} (I)_1 \leq \texttt{src} (I)_1 \leq \texttt{upperb} (I)_1$
  - and so forth.
  That is, dst (I) is set to 255 (all 1 -bits) if src (I) is within the specified 1D, 2D, 3D, ... box and 0 otherwise.
  When the lower and/or upper boundary parameters are scalars, the indexes (I) at lowerb and upperb in the above formulas should be omitted.
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接下來, RGB2HSV

colorInRange.h

colorInRange.cpp

void ImgProc::RGB2HSV(){    Mat dst = RGB2HSV(m_src);    namedWindow("HSV", CV_WINDOW_NORMAL);    cv::imshow("HSV", dst);}Mat ImgProc::RGB2HSV(const Mat& src){    assert(src.type() == CV_8UC3);     Mat dst;    cv::cvtColor(src, dst, CV_BGR2HSV);    return dst;}

Form1.cs

private void rGB2HSVToolStripMenuItem_Click(object sender, EventArgs e){    m_ip.RGB2HSV();}

測試RGB2HSV

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接下來, 測試BGR抽離

colorInRange.h

colorInRange.cpp

void ImgProc::splitColorBGR(){    vector<Mat> spl = splitColor(m_src);    namedWindow("spl1", CV_WINDOW_NORMAL);    namedWindow("spl2", CV_WINDOW_NORMAL);    namedWindow("spl3", CV_WINDOW_NORMAL);    cv::imshow("spl1", spl[0]);            //b    cv::imshow("spl2", spl[1]);            //g    cv::imshow("spl3", spl[2]);            //r}vector<Mat> ImgProc::splitColor(const Mat& src){    vector<Mat> dst;    cv::split(src, dst);    return dst;}

Form1.cs

private void splitRGBToolStripMenuItem_Click(object sender, EventArgs e){    m_ip.splitColorBGR();}

測試結果1 (BGR抽離)

測試結果2 (BGR抽離)

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接下來, 要測試輸出R,G,B三個矩陣的像素值到一個或三個txt檔案[5]

colorInRange.h

colorInRange.cpp

// 輸出RGB像素    void ImgProc::outputTxtRGB(wchar_t* fileRed, wchar_t* fileGreen, wchar_t* fileBlue)    {        wstring wsR(fileRed);        wstring wsG(fileGreen);        wstring wsB(fileBlue);        string nameR = ImgProc::WstringToString(wsR);        string nameG = ImgProc::WstringToString(wsG);        string nameB = ImgProc::WstringToString(wsB);        outputTxtRGB(m_src, nameR.c_str(), nameG.c_str(), nameB.c_str() );        //cv::FileStorage file(name.c_str(), cv::FileStorage::WRITE);        //file << m_src;    }    void ImgProc::outputTxtRGB(const Mat& src, const char* fileRed, const char* fileGreen, const char* fileBlue)    {        ofstream foutRed, foutGreen, foutBlue;        foutRed.open(fileRed, std::ios_base::out);        foutGreen.open(fileGreen, std::ios_base::out);        foutBlue.open(fileBlue, std::ios_base::out);         if (!foutRed)            return;        if (!foutGreen)            return;        if (!foutBlue)            return;          for (int i = 0; i< src.rows; i++)        {            for (int j = 0; j<src.cols; j++)            {                foutBlue  << setw(3) << (int)src.at<cv::Vec3b>(i, j)[0] << " ";                foutGreen << setw(3) << (int)src.at<cv::Vec3b>(i, j)[1] << " ";                foutRed   << setw(3) << (int)src.at<cv::Vec3b>(i, j)[2] << " ";            }            foutBlue << endl;            foutGreen << endl;            foutRed << endl;        }         foutBlue.close();        foutGreen.close();        foutRed.close();    }

Form1.cs

private void outputRGBTextFileToolStripMenuItem_Click(object sender, EventArgs e)        {            using (SaveFileDialog sfdR = new SaveFileDialog())            using (SaveFileDialog sfdG = new SaveFileDialog())            using (SaveFileDialog sfdB = new SaveFileDialog())            {                sfdR.Filter = "Text File|*.txt|Csv File|*.csv";                sfdR.Title = "輸出Red純文字檔案";                sfdG.Filter = "Text File|*.txt|Csv File|*.csv";                sfdG.Title = "輸出Green純文字檔案";                sfdB.Filter = "Text File|*.txt|Csv File|*.csv";                sfdB.Title = "輸出Blue純文字檔案";                 if (sfdR.ShowDialog() == System.Windows.Forms.DialogResult.OK &                     sfdG.ShowDialog() == System.Windows.Forms.DialogResult.OK &                    sfdB.ShowDialog() == System.Windows.Forms.DialogResult.OK)                {                    unsafe                    {                        fixed (char* fileR = sfdR.FileName)                        fixed (char* fileG = sfdG.FileName)                        fixed (char* fileB = sfdB.FileName)                        {                            m_ip.outputTxtRGB(fileR, fileG, fileB);                        }                    }                }            }        }

Red channel

Green channel

Blue channel

MATLAB驗證

下載範例

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接下來, 測試HSV抽離出來並輸出純文字檔案[7]

Different applications use different scales for HSV. For example gimp uses H = 0-360, S = 0-100 and V = 0-100. But OpenCV uses H: 0 - 180, S: 0 - 255, V: 0 - 255

以下為wiki HSL和HSV幾何示意圖[8]

H channel

MATLAB驗證

S channel

MATLAB驗證

V channel

MATLAB驗證

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所以, 接下來可以套用在HSV顏色範圍內的遮罩

colorInRange.h

#include <wchar.h>#include <opencv2\highgui\highgui.hpp>#include <opencv2\imgproc\imgproc.hpp>#include <fstream>#include <iomanip> #pragma once using namespace std;using namespace cv; namespace CVision{    public ref class ImgProc    {    public:        void runColorInRangeHSV(double minH, double maxH, double minS, double maxS, double minV, double maxV);    // 執行HSV顏色範圍內像素        void outputTxtHSV(wchar_t* fileH, wchar_t* fileS, wchar_t* fileV);                                        // 輸出HSV像素        void outputTxtRGB(wchar_t* fileRed, wchar_t* fileGreen, wchar_t* fileBlue);                                  // 輸出RGB像素        void splitColorBGR();        void RGB2HSV();        void runColorInRangeRGB(UINT minR, UINT maxR, UINT minG, UINT maxG, UINT minB, UINT maxB);                // 執行RGB顏色範圍內像素        bool imread(wchar_t* filename);             bool imshow();        ImgProc();        ~ImgProc();     private:        Mat colorInRangeHSV(const Mat& src, double minH, double maxH, double minS, double maxS, double minV, double maxV);    // 篩選HSV顏色範圍內像素        void outputTxtHSV(const Mat& src, const char* fileH, const char* fileS, const char* fileV);               // 輸出HSV像素        void outputTxtRGB(const Mat& src, const char* fileRed, const char* fileGreen, const char* fileBlue);      // 輸出RGB像素          vector<Mat> splitColor(const Mat& src);        Mat RGB2HSV(const Mat& src);        Mat colorInRangeRGB(const Mat& src, UINT minR, UINT maxR, UINT minG, UINT maxG, UINT minB, UINT maxB);    // 篩選RGB顏色範圍內像素        std::string WstringToString(const std::wstring str);     };     ImgProc::ImgProc()    {    }     ImgProc::~ImgProc()    {    }  }

colorInRange.cpp

// 執行HSV顏色範圍內像素void ImgProc::runColorInRangeHSV(double minH, double maxH, double minS, double maxS, double minV, double maxV){    Mat dst;    Mat mask;        cvtColor(m_src, dst, CV_BGR2HSV);    mask = colorInRangeHSV(dst, minH, maxH, minS, maxS, minV, maxV);    if (!mask.data)        return;     // Show source image    namedWindow("color in range of HSV", CV_WINDOW_NORMAL);    cv::imshow("color in range of HSV", mask);}// 篩選HSV顏色範圍內像素Mat ImgProc::colorInRangeHSV(const Mat& src, double minH, double maxH, double minS, double maxS, double minV, double maxV){    assert(src.type() == CV_8UC3);    Mat mask;    //inRange(src, Scalar(minH, minS, minV), Scalar(maxH, maxS, maxV), mask);    inRange(src, Scalar_<double>(minH, minS, minV), Scalar_<double>(maxH, maxS, maxV), mask);    return mask;}