Java Code Examples for org.opencv.core.Mat#width()

/**
 * 
* @Title: detectMany 
* @Description: 检测多人图片，返回检测的人脸区域对象
* @param mImgSRC
* @return
* MatOfRect
 */
public static MatOfRect detectMany(Mat mImgSRC) {
	
	if(mImgSRC.empty()) {
		LOG.info("检测多人图片检测时没有找到图片");
		return null;
	}
	// 人脸检测器文件的所在路径的文件夹名称数组
	String [] pathKey = {ServletContextHolder.getOpenCVHaarcascades(), "haarcascade_frontalface_alt.xml"};
	CascadeClassifier cascade = new CascadeClassifier(FileUtils.buildFilePath(pathKey));
	if(cascade.empty()) {
		LOG.info("人脸检测级联加载器为null");
		return null;
	}
	// 记录搜索到的人脸区域
	MatOfRect mOfRect = new MatOfRect();
	// 用于计算缩放比例
	int scaledWidth = mImgSRC.width();
	detectManyObject(mImgSRC, cascade, mOfRect, scaledWidth);
	if(mOfRect.toArray().length <= 0) {
		LOG.info("没有检测到人脸...");
		return null;
	}
	return mOfRect;
}
 

public MatOfPoint2f getPoint(Bitmap bitmap) {

        Mat src = ImageUtils.bitmapToMat(bitmap);

        // Downscale image for better performance.
        double ratio = DOWNSCALE_IMAGE_SIZE / Math.max(src.width(), src.height());
        Size downscaledSize = new Size(src.width() * ratio, src.height() * ratio);
        Mat downscaled = new Mat(downscaledSize, src.type());
        Imgproc.resize(src, downscaled, downscaledSize);

        List<MatOfPoint2f> rectangles = getPoints(downscaled);
        if (rectangles.size() == 0) {
            return null;
        }
        Collections.sort(rectangles, AreaDescendingComparator);
        MatOfPoint2f largestRectangle = rectangles.get(0);
        MatOfPoint2f result = MathUtils.scaleRectangle(largestRectangle, 1f / ratio);
        return result;
    }
 

protected <SFIRBS> String doRead(SFIRBS from) {
  try {
    String text = "";
    if (from instanceof Mat) {
      Mat img = ((Mat) from).clone();
      if (!img.empty()) {
        img = SXOpenCV.optimize(img, options.factor(), options.resizeInterpolation());
        byte[] bytes = new byte[img.width() * img.height()];
        int n = img.get(0, 0, bytes);
        text = getTesseractAPI().doOCR(img.width(), img.height(), ByteBuffer.wrap(bytes), null, 8);
      } else {
        return "";
      }
    } else {
      BufferedImage bimg = SXOpenCV.optimize(Element.getBufferedImage(from), options.factor(), options.resizeInterpolation());
      text = getTesseractAPI().doOCR(bimg);
    }
    return text.trim().replace("\n\n", "\n");
  } catch (TesseractException e) {
    Debug.error("OCR: read: Tess4J: doOCR: %s", e.getMessage());
    return "";
  }
}
 

/**
 * 垂直旋转90度
 * 
 * @param mat
 * @return
 */
public static Mat rotation(Mat mat) {
	int len, wid;
	if (mat.width() > mat.height()) {
		len = mat.width();
		wid = mat.height();
	} else {
		len = mat.height();
		wid = mat.width();
	}

	// 得到旋转矩阵算子
	Mat matrix = Imgproc.getRotationMatrix2D(new Point(len / 2, len / 2), 90, 1);

	Mat CorrectImg = new Mat(new Size(len, len), mat.type());

	Imgproc.warpAffine(mat, CorrectImg, matrix, CorrectImg.size(), Imgproc.INTER_LINEAR, 0, new Scalar(0, 0, 0));

	int extend = 18;

	Mat temp = new Mat(CorrectImg, new Rect(0, len - wid + extend, len, wid - 2 * extend));

	return temp;
}
 

/**
 * Rotate an image by an angle (counterclockwise)
 *
 * @param image Transform matrix
 * @param angle Angle to rotate by (counterclockwise) from -360 to 360
 */
public static void rotate(Mat image, double angle) {
    //Calculate size of new matrix
    double radians = Math.toRadians(angle);
    double sin = Math.abs(Math.sin(radians));
    double cos = Math.abs(Math.cos(radians));

    int newWidth = (int) (image.width() * cos + image.height() * sin);
    int newHeight = (int) (image.width() * sin + image.height() * cos);

    // rotating image
    Point center = new Point(newWidth / 2, newHeight / 2);
    Mat rotMatrix = Imgproc.getRotationMatrix2D(center, angle, 1.0); //1.0 means 100 % scale

    Size size = new Size(newWidth, newHeight);
    Imgproc.warpAffine(image, image, rotMatrix, image.size());
}
 

private Mat possibleImageResizeMask(Image image, Mat what) {
  Mat mask = image.getMask().getContent();
  double factor = mask.width() / what.width();
  if (factor > 0.1 && factor != 1) {
    mask = SXOpenCV.cvResize(mask.clone(), factor, Image.Interpolation.CUBIC);
  }
  List<Mat> mats = SXOpenCV.extractMask(mask, false);
  return mats.get(1);
}
 

public static void showCV(Mat image) {
  String title = "show Mat";
  HighGui.namedWindow(title);
  Screen screen = Screen.getPrimaryScreen();
  int x = (screen.w - image.width()) / 2;
  int y = (screen.h - image.height()) / 2;
  HighGui.moveWindow(title, x, y);
  HighGui.imshow(title, image);
  HighGui.waitKey(3000);
}
 

public Result[] zxing( Mat inputImage ) throws ChecksumException, FormatException {

        int w = inputImage.width();
        int h = inputImage.height();

        Mat southEast;

        if (mBugRotate) {
            southEast = inputImage.submat(h-h/4 , h , 0 , w/2 - h/4 );
        } else {
            southEast = inputImage.submat(0, h / 4, w / 2 + h / 4, w);
        }

        Bitmap bMap = Bitmap.createBitmap(southEast.width(), southEast.height(), Bitmap.Config.ARGB_8888);
        org.opencv.android.Utils.matToBitmap(southEast, bMap);
        southEast.release();
        int[] intArray = new int[bMap.getWidth()*bMap.getHeight()];
        //copy pixel data from the Bitmap into the 'intArray' array
        bMap.getPixels(intArray, 0, bMap.getWidth(), 0, 0, bMap.getWidth(), bMap.getHeight());

        LuminanceSource source = new RGBLuminanceSource(bMap.getWidth(), bMap.getHeight(),intArray);

        BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(source));

        Result[] results = {};
        try {
            results = qrCodeMultiReader.decodeMultiple(bitmap);
        }
        catch (NotFoundException e) {
        }

        return results;

    }
 

FPClassification findAngles(Mat image, Rect rect){
		double imageCenterX = (image.width()/2);
		double faceCenterX = rect.x + (rect.width/2);
		double distanceFromCenterX = Math.abs(imageCenterX - faceCenterX);
		double angleX = (distanceFromCenterX/imageCenterX) * CAMERA_FOV_VERT/2;

		System.out.println("Image CenterX: "+imageCenterX +
				   "\nRect X: "+rect.x +
				   "\nRect Width: "+rect.width +
				   "\nFace Center: "+faceCenterX+
				   "\nDistance From Center: "+distanceFromCenterX+
				   "\nAngle: "+angleX);

		double imageCenterY = (image.height()/2);
		double faceCenterY = rect.y + (rect.height/2);
		double distanceFromCenterY = Math.abs(imageCenterY - faceCenterY);
		double angleY = (distanceFromCenterY/imageCenterY) * CAMERA_FOV_HORIZ/2;

		System.out.println("Image CenterY: "+imageCenterY +
				   "\nRect Y: "+rect.y +
				   "\nRect Height: "+rect.height +
				   "\nFace Center: "+faceCenterY+
				   "\nDistance From Center: "+distanceFromCenterY+
				   "\nAngle: "+angleY);

		FPClassification ret = new FPClassification();
		ret.angleX = angleX;
		ret.angleY = angleY;
		ret.detected = true;

		if(imageCenterX > rect.x)
			ret.angleX *= -1;
		if(imageCenterY < rect.y)
			ret.angleY *= -1;
		return ret;
}
 

/**
 * 把opencv的灰度图Mat转化为List<List<Double>> , 即数组对象
 * 
 * @param gray
 * @param b
 *            true 表示List<Double>是每一列的灰度值，否则List<Double>是每一行的灰度值
 * @return
 */
public static List<List<Double>> MatPixelToList(Mat gray, boolean b) {
	if (gray == null) {
		throw new RuntimeException("不能传入空对象");
	}
	List<List<Double>> result = new ArrayList<>();
	int x, y;
	int i, j;
	double[] value;
	if (b) {
		// List<Double>是每一列的灰度值
		x = gray.width();
		y = gray.height();
	} else {
		// List<Double>是每一行的灰度值
		x = gray.height();
		y = gray.width();
	}

	for (i = 0; i < x; i++) {
		List<Double> oneLine = new ArrayList<>();
		for (j = 0; j < y; j++) {
			if (b) {
				value = gray.get(j, i);
			} else {
				value = gray.get(i, j);
			}

			oneLine.add(value[0]);
		}
		result.add(oneLine);
	}

	return result;
}
 

/**
 * @param image the {@link Mat} to scale
 * @param scaleFactor the scale factor (<1 will scale down, >1 will scale up, 1 = 100%)
 * @return a {@link Mat} which is a version of the original image scaled by the given factor
 */
public static Mat scaleImage(Mat image, double scaleFactor) {
  Mat resizedImage = new Mat();
  Size sz = new Size(image.width() * scaleFactor, image.height() * scaleFactor);
  Imgproc.resize(image, resizedImage, sz);
  return resizedImage;
}
 

static BufferedImage matToBufferedImage(Mat matBGR) {
	final BufferedImage image = new BufferedImage(matBGR.width(), matBGR.height(), BufferedImage.TYPE_3BYTE_BGR);
	final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
	matBGR.get(0, 0, targetPixels);

	return image;
}
 

@Test
public void testDetectManyObject() {
	String opencvDLL = "G:/java/JavaProjectRelease/classchecks/src/main/webapp/WEB-INF/dll/x64/opencv_java320.dll";
	System.load(opencvDLL);
	
	String haarcascade = "haarcascade_frontalface_alt.xml";
	
	
	CascadeClassifier cascade = new CascadeClassifier(XMLFilePath + haarcascade);
	
	Mat src = Imgcodecs.imread(imageDir + "/split/14.jpg");
	
	MatOfRect objects = new MatOfRect();
	int scaledWidth = src.width();
	
	DetectObject.detectManyObject(src, cascade, objects, scaledWidth);
	
	Rect [] rects = objects.toArray();
	int i = 0;
	for(Rect r : rects) {
		/*Imgproc.rectangle(src, new Point(r.x-100 , r.y-100 ), 
				new Point(r.x + r.width + 80, 
						r.y + r.height + 80), new Scalar(0, 0, 255), 3);*/
		Imgproc.rectangle(src, r.tl(), 
				r.br(), new Scalar(0, 0, 255), 3);
		/*r.width += 120;
		r.height += 120;
		r.x -= 100;
		r.y -= 100;
		System.out.println(r);
		Mat roi = new Mat(src, r);
		Imgcodecs.imwrite("e:/classchecks/2017417/split/"+i+".jpg", roi);
		i ++;*/
	}
	Imgcodecs.imwrite("e:/classchecks/2017417/dectctManyObject.jpg", src);
	//Imgcodecs.imwrite("e:/classchecks/dectctManyObject.jpg", src);
}
 

public Result[] zxing( Mat inputImage ) throws ChecksumException, FormatException {

        int w = inputImage.width();
        int h = inputImage.height();

        Mat southEast;

        if (mBugRotate) {
            southEast = inputImage.submat(h-h/4 , h , 0 , w/2 - h/4 );
        } else {
            southEast = inputImage.submat(0, h / 4, w / 2 + h / 4, w);
        }

        Bitmap bMap = Bitmap.createBitmap(southEast.width(), southEast.height(), Bitmap.Config.ARGB_8888);
        org.opencv.android.Utils.matToBitmap(southEast, bMap);
        southEast.release();
        int[] intArray = new int[bMap.getWidth()*bMap.getHeight()];
        //copy pixel data from the Bitmap into the 'intArray' array
        bMap.getPixels(intArray, 0, bMap.getWidth(), 0, 0, bMap.getWidth(), bMap.getHeight());

        LuminanceSource source = new RGBLuminanceSource(bMap.getWidth(), bMap.getHeight(),intArray);

        BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(source));

        Result[] results = {};
        try {
            results = qrCodeMultiReader.decodeMultiple(bitmap);
        }
        catch (NotFoundException ignored) {
        }
        return results;
    }
 

@Override
public Mat onCameraFrame(Mat originalFrame) {
	try{
		// Image is too big and this requires too much CPU for a phone, so scale everything down...
		Imgproc.resize(originalFrame, _workingFrame, WORKING_FRAME_SIZE);
		final Size workingRatio = new Size(originalFrame.width() / WORKING_FRAME_SIZE.width, originalFrame.height() / WORKING_FRAME_SIZE.height);
		// usefull to see what we're actually working with...
		_workingFrame.copyTo(originalFrame.submat(originalFrame.rows() - _workingFrame.rows(), originalFrame.rows(), 0, _workingFrame.cols()));
		
		if(_trackedBox != null){
			if(_tld == null){ // run the 1st time only
				Imgproc.cvtColor(_workingFrame, _lastGray, Imgproc.COLOR_RGB2GRAY);
				_tld = new Tld(_tldProperties);
				final Rect scaledDownTrackedBox = scaleDown(_trackedBox, workingRatio);
				Log.i(Util.TAG, "Working Ration: " + workingRatio + " / Tracking Box: " + _trackedBox + " / Scaled down to: " + scaledDownTrackedBox);
				try {
					_tld.init(_lastGray, scaledDownTrackedBox);
				}catch(Exception eInit){
			        // start from scratch, you have to select an init box again !
					_trackedBox = null;
					_tld = null;
					throw eInit; // re-throw it as it will be dealt with later
				}
			}else{
				Imgproc.cvtColor(_workingFrame, _currentGray, Imgproc.COLOR_RGB2GRAY);
			
				_processFrameStruct = _tld.processFrame(_lastGray, _currentGray);
				drawPoints(originalFrame, _processFrameStruct.lastPoints, workingRatio, new Scalar(255, 0, 0));
				drawPoints(originalFrame, _processFrameStruct.currentPoints, workingRatio, new Scalar(0, 255, 0));
				drawBox(originalFrame, scaleUp(_processFrameStruct.currentBBox, workingRatio), new Scalar(0, 0, 255));
					
				_currentGray.copyTo(_lastGray);
				
				// overlay the current positive examples on the real image(needs converting at the same time !)
				//copyTo(_tld.getPPatterns(), originalFrame);
			}
		}
	} catch(Exception e) {
        _errMessage = e.getClass().getSimpleName() + " / " + e.getMessage();
        Log.e(Util.TAG, "TLDView PROBLEM", e);
	}

	
	if(_errMessage !=  null){
		Core.putText(originalFrame, _errMessage, new Point(0, 300), Core.FONT_HERSHEY_PLAIN, 1.3d, new Scalar(255, 0, 0), 2);
	}
	
       return originalFrame;
}
 

public static BufferedImage matToBufferedImage (Mat matrix) {		
	if (matrix.channels() == 1) {
		int cols = matrix.cols();
		int rows = matrix.rows();
		int elemSize = (int)matrix.elemSize();
		byte[] data = new byte[cols * rows * elemSize];
		int type;
		matrix.get(0, 0, data);
		switch (matrix.channels()) {
		case 1:
			type = BufferedImage.TYPE_BYTE_GRAY;
			break;
		case 3:
			type = BufferedImage.TYPE_3BYTE_BGR;
			// bgr to rgb
			byte b;
			for (int i = 0; i < data.length; i = i + 3) {
				b = data[i];
				data[i] = data[i + 2];
				data[i + 2] = b;
			}
			break;
		default:
			return null;
		}

		BufferedImage image2 = new BufferedImage(cols, rows, type);
		image2.getRaster().setDataElements(0, 0, cols, rows, data);
		return image2;
	}

	if (matrix.channels() == 3) {
		int width = matrix.width(), height = matrix.height(), channels = matrix.channels();
		byte[] sourcePixels = new byte[width * height * channels];
		matrix.get(0, 0, sourcePixels);
		// create new image and get reference to backing data
		BufferedImage image = new BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR);
		final byte[] targetPixels = ((DataBufferByte)image.getRaster().getDataBuffer()).getData();
		System.arraycopy(sourcePixels, 0, targetPixels, 0, sourcePixels.length);
		return image;
	}

	return null;
}
 

public static  double findMarkerWidth(String imgPath){
    Mat frame = Highgui.imread(imgPath);
    Mat gscale = new Mat();
    Mat blur = new Mat();
    Mat edged = new Mat();

    // convert the image to grayscale, blur it, and detect edges
    if(frame.channels()>1)
        Imgproc.cvtColor(frame, gscale, Imgproc.COLOR_BGR2GRAY);
    else
        gscale = frame;

    Imgproc.GaussianBlur(gscale, blur, new Size(5, 5), 0);
    Imgproc.Canny(blur, edged, 35, 125);

    // find the contours in the edged image and keep the largest one;
    // we'll assume that this is our piece of paper in the image
    List<MatOfPoint> contours = new ArrayList<>();
    Mat hierarchy = new Mat(edged.width(), edged.height(), CvType.CV_8UC1);
    Imgproc.findContours(edged.clone(), contours, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
    int max_idx = 0;

    // if any contour exist...
    if (hierarchy.size().height > 0 && hierarchy.size().width > 0)
    {
        double max_area = 0;
        double area;
        // find the contour with largest area
        for (int idx = 0; idx >= 0; idx = (int) hierarchy.get(0, idx)[0])
        {
            area = Imgproc.contourArea(contours.get(idx));
            if(area > max_area){
                max_area = area;
                max_idx = idx;
            }
            Imgproc.drawContours(frame, contours, idx, new Scalar(0, 0, 255));
        }

        //Riz: Save File
        //Imgproc.drawContours(frame, contours, max_idx, new Scalar(250, 0, 0));
        byte[] bytes = new byte[ frame.rows() * frame.cols() * frame.channels() ];


        File file = new File(CameraActivity.activity.getExternalFilesDir(null), "pic_contour"+ Integer.toString(pic_count) + ".jpg");
        pic_count++;

        Boolean bool = null;
        String filename = file.toString();
        bool = Highgui.imwrite(filename, frame);

        if (bool == true)
            Log.d(LOG_TAG, "SUCCESS writing image to external storage");
        else
            Log.d(LOG_TAG, "Fail writing image to external storage");

        Log.i(LOG_TAG, "Max Area: " + Double.toString(max_area));
    }
    else{
        Log.e(LOG_TAG, "No Contour Found!");
    }

    MatOfPoint2f newPoint = new MatOfPoint2f(contours.get(max_idx).toArray());

    return Imgproc.arcLength(newPoint, true);
}
 

/**
 * OpenCVで
 * @param bmpOrig
 */
private void extractObject(Bitmap bmpOrig) {

    // まずオリジナルのビットマップを表示
    mImageView1.setImageBitmap(bmpOrig);
    // 高さと幅を取得
    int height = bmpOrig.getHeight();
    int width = bmpOrig.getWidth();
    
    // OpenCVオブジェクトの用意
    Mat matOrig = new Mat(height,width,CvType.CV_8UC4); 
    // ビットマップをOpenCVオブジェクトに変換
    Utils.bitmapToMat(bmpOrig, matOrig);
    
    /**
     * グレースケールに変換
     */
    Mat matGray = new Mat(height,width,CvType.CV_8UC1);
    Imgproc.cvtColor(matOrig, matGray, Imgproc.COLOR_RGB2GRAY);
    // 表示
    Bitmap bmpGray = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
    Utils.matToBitmap(matGray, bmpGray);
    mImageView2.setImageBitmap(bmpGray);

    /**
     * グレースケール→二値化    
     */
    Mat matBlack = new Mat(height,width,CvType.CV_8UC1);
    // 二値化
    Imgproc.threshold(matGray, matBlack, sTH, 255, Imgproc.THRESH_BINARY);
    // 表示
    Bitmap bmpBlack = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
    Utils.matToBitmap(matBlack, bmpBlack);
    mImageView3.setImageBitmap(bmpBlack);

    /**
     * グレースケール→二値化→輪郭塗りつぶし
     */
    // 輪郭を抽出する
    ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Mat hierarchy = new Mat(matBlack.height(),matBlack.width(),CvType.CV_8UC1);
    int mode = Imgproc.RETR_EXTERNAL;
    int method = Imgproc.CHAIN_APPROX_SIMPLE;

    // 輪郭を抽出する
    Imgproc.findContours(matBlack, contours, hierarchy, mode, method);
    // 輪郭を描く
    Scalar color = new Scalar(255.f, 0.f, 0.f, 0.f);
    Imgproc.drawContours(matBlack, contours, -1, color, 2);
    // 表示
    Bitmap bmpContour = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
    org.opencv.android.Utils.matToBitmap(matBlack, bmpContour);
    mImageView4.setImageBitmap(bmpContour);

    // 抽出した輪郭の内部を塗りつぶす
    Imgproc.drawContours(matBlack, contours, -1, color, -1);
    // 表示
    Bitmap bmpContour2 = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
    org.opencv.android.Utils.matToBitmap(matBlack, bmpContour2);
    mImageView5.setImageBitmap(bmpContour2);

    
    /**
     * 二値化したマスクを使ってオブジェクトだけをとりだす
     */
    Mat matObject = new Mat(height,width,CvType.CV_8UC4); 
    Core.add(matObject, matOrig, matObject, matBlack);  
    // 表示
    Bitmap bmpObject = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
    org.opencv.android.Utils.matToBitmap(matObject, bmpObject);
    mImageView6.setImageBitmap(bmpObject);

    /**
     * とりだしたオブジェクトに外接する矩形のみをBMPとして抜き出す
     */
    Rect rect = Imgproc.boundingRect(contours.get(0));
    Mat matCut = new Mat(matObject, rect);
    // 表示
    Bitmap bmpCut = Bitmap.createBitmap(matCut.cols(), matCut.rows(), Bitmap.Config.ARGB_8888);
    org.opencv.android.Utils.matToBitmap(matCut, bmpCut);
    mImageView7.setImageBitmap(bmpCut);
}
 

/**
 * Finds a template image in a source image. Throws an exception when the
 * image wasn't found or the desired accuracy couldn't be met.
 *
 * @param sourceMat The source image.
 * @param templateMat The template image to find in the source image.
 * @param desiredAccuracy The desired accuracy of the find operation as a
 * number between 0 and 1.
 * @return An ImageFinderResult object that stores the rectangle of the
 * found image and desired accuracy.
 */
private ImageFinderResult findImage(Mat sourceMat, Mat templateMat, double desiredAccuracy) {
    if (sourceMat.width() < templateMat.width() || sourceMat.height() < templateMat.height()) {
        throw new UnsupportedOperationException("The template image is larger than the source image. Ensure that the width and/or height of the image you are trying to find do not exceed the dimensions of the source image.");
    }

    Mat result = new Mat(sourceMat.rows() - templateMat.rows() + 1, sourceMat.rows() - templateMat.rows() + 1, CvType.CV_32FC1);
    int intMatchingMethod;

    switch (this.matchingMethod) {
        case MM_CORELLATION_COEFF:
            intMatchingMethod = Imgproc.TM_CCOEFF_NORMED;
            break;
        case MM_CROSS_CORELLATION:
            intMatchingMethod = Imgproc.TM_CCORR_NORMED;
            break;
        default:
            intMatchingMethod = Imgproc.TM_SQDIFF_NORMED;
    }

    Imgproc.matchTemplate(sourceMat, templateMat, result, intMatchingMethod);
    MinMaxLocResult minMaxLocRes = Core.minMaxLoc(result);

    double accuracy = 0;
    Point location = null;

    if (this.matchingMethod == MatchingMethod.MM_SQUARE_DIFFERENCE) {
        accuracy = 1 - minMaxLocRes.minVal;
        location = minMaxLocRes.minLoc;
    } else {
        accuracy = minMaxLocRes.maxVal;
        location = minMaxLocRes.maxLoc;
    }

    if (accuracy < desiredAccuracy) {
        throw new ImageNotFoundException(
                String.format(
                        "Failed to find template image in the source image. The accuracy was %.2f and the desired accuracy was %.2f",
                        accuracy,
                        desiredAccuracy),
                new Rectangle((int) location.x, (int) location.y, templateMat.width(), templateMat.height()),
                accuracy);
    }

    if (!minMaxLocResultIsValid(minMaxLocRes)) {
        throw new ImageNotFoundException(
                "Image find result (MinMaxLocResult) was invalid. This usually happens when the source image is covered in one solid color.",
                null,
                null);
    }

    Rectangle foundRect = new Rectangle(
            (int) location.x,
            (int) location.y,
            templateMat.width(),
            templateMat.height());

    return new ImageFinderResult(foundRect, accuracy);
}
 

/**
 * 切割
 * 
 * @param src
 * @return
 */
public static List<Mat> cutUtils(Mat src) {
	if (src.channels() != 1) {
		src = GrayUtils.grayColByPartAdapThreshold(src);
		src = BinaryUtils.binaryzation(src);
	}

	if (src.height() > src.width()) {
		src = RotationUtils.rotation(src);
	}

	// 求最大轮廓的点集
	Point[] points = ContoursUtils.useApproxPolyDPFindPoints(GeneralUtils.canny(src));

	src = PaintUtils.paintCircle(src, points, 10, new Scalar(255, 255, 255));

	// 清除最大的连通域
	src = RemoveNoiseUtils.findMaxConnected(src, 255);

	// 降噪
	src = RemoveNoiseUtils.connectedRemoveNoise(src, 100);

	// 水平切割
	List<Mat> xList = cutUtilsX(src);

	// 垂直切割
	List<Integer> yPoint = cutUtilsY(xList.get(0));

	// 最终的结果集
	List<Mat> result = new ArrayList<>();

	int xlen = xList.size();
	for (int i = 0; i < xlen; i++) {
		if (xlen > 1 && i == 0) {
			continue;
		}
		for (int j = 1; j < yPoint.size(); j++) {
			Mat temp = new Mat(xList.get(i),
					new Rect(yPoint.get(j - 1), 0, yPoint.get(j) - yPoint.get(j - 1), xList.get(i).height()));
			result.add(temp);
		}

	}

	return result;

}