OpenCV顏色檢測爲黃色

Question

這是一個來自OpenCV ColorBlobDetectionActivity.java示例的程序，我試圖對其進行修改，以便在觸摸屏幕時檢測黃色物體，但它始終只檢測到黑色物體，即使我指定了顏色標量爲黃色。我已在我認爲相關的地方發表了「通知」的評論。

package com.example.road_guiding; 

import java.util.List; 

import org.opencv.android.BaseLoaderCallback; 
import org.opencv.android.CameraBridgeViewBase; 
import org.opencv.android.OpenCVLoader; 
import org.opencv.core.Core; 
import org.opencv.core.CvType; 
import org.opencv.core.Mat; 
import org.opencv.core.Rect; 
import org.opencv.core.Scalar; 
import org.opencv.core.Size; 
import org.opencv.imgproc.Imgproc; 

import android.app.Activity; 
import android.os.Bundle; 
import android.util.Log; 
import android.view.MotionEvent; 
import android.view.View; 



public class ColorBlobDetectionActivity extends Activity implements View.OnTouchListener, CameraBridgeViewBase.CvCameraViewListener2 { 
// private static final String TAG = "OCVSample::Activity"; 
    private Scalar CONTOUR_COLOR; 
    private Scalar mBlobColorHsv; 
    private Scalar mBlobColorRgba; 

    //NOTICE 
    private Scalar temp;  

    private ColorBlobDetector mDetector; 
    private boolean mIsColorSelected = false; 
    private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) { 
     public void onManagerConnected(int paramAnonymousInt) { 
      switch (paramAnonymousInt) { 
      default: 
       super.onManagerConnected(paramAnonymousInt); 
//    Log.i("OCVSample::Activity", "OpenCV loaded successfully"); 
       ColorBlobDetectionActivity.this.mOpenCvCameraView.enableView(); 
       ColorBlobDetectionActivity.this.mOpenCvCameraView.setOnTouchListener(ColorBlobDetectionActivity.this); 

       return; 
      } 

     } 
    }; 
    private CameraBridgeViewBase mOpenCvCameraView; 
    private Mat mRgba; 
// private Size SPECTRUM_SIZE; 
// private Mat mSpectrum; 

    public ColorBlobDetectionActivity() { 
     Log.i("OCVSample::Activity", "Instantiated new " + getClass()); 
    } 

    private Scalar converScalarHsv2Rgba(Scalar paramScalar) { 
     Mat localMat = new Mat(); 
     Imgproc.cvtColor(new Mat(1, 1, CvType.CV_8UC3, paramScalar), localMat, 71, 4); 
     return new Scalar(localMat.get(0, 0)); 
    } 

    public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame paramCvCameraViewFrame) { 
     this.mRgba = paramCvCameraViewFrame.rgba(); // mRbga = input frame with color 

     if (this.mIsColorSelected) { 
      this.mDetector.process(this.mRgba); 

      //contour info is ready in detector 
      List colorContour = this.mDetector.getContours(); 
//   Log.e("OCVSample::Activity", "Contours count: " + localList.size()); 
      Imgproc.drawContours(this.mRgba, colorContour, -1, this.CONTOUR_COLOR); //draw contour around detected area  

      this.mRgba.submat(4, 68, 4, 68).setTo(this.mBlobColorRgba); 

//   Producing spectrum 
//   Mat localMat = this.mRgba.submat(4, 4 + this.mSpectrum.rows(), 70, 70 + this.mSpectrum.cols()); 
//   this.mSpectrum.copyTo(localMat); 
     } 
     return this.mRgba; 
    } 

    public void onCameraViewStarted(int paramInt1, int paramInt2) { 
     this.mRgba = new Mat(paramInt2, paramInt1, CvType.CV_8UC4); //width - - the width of the frames that will be delivered 
     this.mDetector = new ColorBlobDetector(); 
     this.mBlobColorRgba = new Scalar(255.0); 
     this.mBlobColorHsv = new Scalar(255.0); 
     this.CONTOUR_COLOR = new Scalar(255.0, 0.0, 0.0, 255.0); //Specfiy the color of contour 

     //NOTICE 
     this.temp = new Scalar (237.0, 169.0, 50.0, 255.0); 

     //yellow to be used: 
//  this.mBlobColorRgba.val[0] = 237; 
//  this.mBlobColorRgba.val[1] = 169; 
//  this.mBlobColorRgba.val[2] = 50; 
//  this.mBlobColorRgba.val[3] = 255; 


//  this.mSpectrum = new Mat(); 
//  this.SPECTRUM_SIZE = new Size(200.0, 64.0); 
    } 

    public void onCreate(Bundle paramBundle) { 
//  Log.i("OCVSample::Activity", "called onCreate"); 
     super.onCreate(paramBundle); 
//  requestWindowFeature(1); // do not show app title 
//  getWindow().addFlags(128); 
     setContentView(R.layout.activity_color_blob_detection); 
     this.mOpenCvCameraView = ((CameraBridgeViewBase) findViewById(R.id.HelloOpenCvView)); 
     this.mOpenCvCameraView.setCvCameraViewListener(this); 
    } 

    public boolean onTouch(View paramView, MotionEvent paramMotionEvent) 
     { 
     int cameraViewWidth = this.mRgba.cols(); // cameraViewWidth = i 
     int cameraViewHeight = this.mRgba.rows(); // cameraViewHeight = j 
     int xOffset = (this.mOpenCvCameraView.getWidth() - cameraViewWidth)/2; 
     int yOffset = (this.mOpenCvCameraView.getHeight() - cameraViewHeight)/2; 
     int touchX = (int)paramMotionEvent.getX() - xOffset; 
     int touchY = (int)paramMotionEvent.getY() - yOffset; 

     //  Log.i("OCVSample::Activity", "Touch image coordinates: (" + n = touchX + ", " + i1=touchY + ")"); 
     if ((touchX < 0) || (touchY < 0) || (touchX > cameraViewWidth) || (touchY > cameraViewHeight)) { 
      return false; 
     } 

     Rect touchedRect = new Rect(); 
     if (touchX > 4) { 
      touchedRect.x = touchX - 4; 
      touchedRect.y = touchY - 4; 
      touchedRect.width = touchX + 4 - touchedRect.x; 
     } 

     for (int i5 = touchY + 4 - touchedRect.y;; i5 = cameraViewHeight - touchedRect.y) { 
      touchedRect.height = i5; 

//   Mat touchedRegionRgba = this.mRgba.submat(touchedRect); 
      Mat touchedRegionRgba = new Mat(); 

      //NOTICE 
      Imgproc.cvtColor(new Mat(1, 1, CvType.CV_8UC3, temp), touchedRegionRgba, 71, 0); 

      Mat touchedRegionHsv = new Mat(); 

      Imgproc.cvtColor(touchedRegionRgba, touchedRegionHsv, Imgproc.COLOR_RGB2HSV_FULL); //67 
      this.mBlobColorHsv = Core.sumElems(touchedRegionHsv); //calculate average color of touched region 
      int pixelCount = touchedRect.width * touchedRect.height; 
      for (int i = 0; i < this.mBlobColorHsv.val.length; i++) { 
       double[] arrayOfDouble = this.mBlobColorHsv.val; 
       arrayOfDouble[i] /= pixelCount; 
      } 
      touchedRegionRgba.release(); 
      touchedRegionHsv.release(); 

     break; 
     } 

     this.mBlobColorRgba = converScalarHsv2Rgba(this.mBlobColorHsv); 

//  Log.i("OCVSample::Activity", "Touched rgba color: (" + this.mBlobColorRgba.val[0] + ", " + this.mBlobColorRgba.val[1] + ", " + this.mBlobColorRgba.val[2] + ", " + this.mBlobColorRgba.val[3] + ")"); 

     this.mDetector.setHsvColor(this.mBlobColorHsv); 

//  Imgproc.resize(this.mDetector.getSpectrum(), this.mSpectrum, this.SPECTRUM_SIZE); 
     this.mIsColorSelected = true; 
     return false; 
     } 

    public void onDestroy() { 
     super.onDestroy(); 
     if (this.mOpenCvCameraView != null) { 
      this.mOpenCvCameraView.disableView(); 
     } 
    } 

    public void onPause() { 
     super.onPause(); 
     if (this.mOpenCvCameraView != null) { 
      this.mOpenCvCameraView.disableView(); 
     } 
    } 

    public void onResume() { 
     super.onResume(); 
     OpenCVLoader.initAsync("2.4.3", this, this.mLoaderCallback); 
    } 

    public void onCameraViewStopped() { 
     this.mRgba.release(); 
    } 
} 

任何幫助將不勝感激，謝謝！

Answer 1

對不起，我不知道Java，但我可以建議檢測「黃色」顏色的一般邏輯。您應該將RGB圖像轉換爲YUV圖像，然後均衡Y通道。由於Y通道用於亮度，所以通過這樣做可以減少光照變化的影響。

- 然後將圖像轉換回RGB從YUV - 現在將圖像轉換爲HSV。現在嘗試只計算可能代表「黃色」顏色的那些像素。爲此，使用以下條件：

1. 像素應具有S>0（或接近0的某個其它值），以消除這在計算研究創建問題白色像素。
2. 像素應具有V>0刪除「黑像素」具有V = 0
3. 如果H> 22 && H<37然後增加yellowPixelCount由1

- 所以，按照上述提到的過程中，將可以計算圖像中的「黃色」像素。而且，如果計數大於閾值，則可以預測它是「黃色」顏色。

PS：不要忘了算像素的總數其fullfill標準1 & 2，這樣就可以使用該值找到黃色成分的百分比來預測圖像是否有黃色或沒有。

if (condition 1 & 2 satisfied) 
{ 
    totalPixelCount++; 
    if(condition 3 satisfied) 
    { 
     yellowPixelCount 
    } 
} 

% of yellow componet = yellowPixelCount/totalPixelCount*100