2017-12-02 179 views
1

inputImage的OpenCV的抗扭斜的轮廓

enter image description here

ResultImage

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我已经能够过滤最大的轮廓图像中检测令牌。

我已经应用了经纱知觉,但它只是在轮廓的边缘裁剪图像,没有别的。

我想要将检测到的令牌从图像的其余部分中裁剪出来,在保持比例的情况下对其进行去偏斜,以便结果图像应该直立,笔直。然后,我将继续寻找令牌中的斑点来检测其中标记的日期。

private Mat processMat(Mat srcMat) { 
    Mat processedMat = new Mat(); 
    Imgproc.cvtColor(srcMat, processedMat, Imgproc.COLOR_BGR2GRAY); 
    Imgproc.GaussianBlur(processedMat, processedMat, new Size(5, 5), 5); 
    Imgproc.threshold(processedMat, processedMat, 127, 255, Imgproc.THRESH_BINARY); 
    List<MatOfPoint> contours = new ArrayList<>(); 
    Mat hierarchy = new Mat(); 
    Imgproc.findContours(processedMat, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); 

    double maxVal = 0; 
    int maxValIdx = 0; 
    for (int contourIdx = 0; contourIdx < contours.size(); contourIdx++) { 
     double contourArea = Imgproc.contourArea(contours.get(contourIdx)); 
     if (maxVal < contourArea) { 
      maxVal = contourArea; 
      maxValIdx = contourIdx; 
     } 
    } 
    if (!contours.isEmpty()) { 
     Imgproc.drawContours(srcMat, contours, maxValIdx, new Scalar(0,255,0), 3); 
     Rect rect = Imgproc.boundingRect(contours.get(maxValIdx)); 
     Log.e("rect", "" + rect); 
     int top = srcMat.height(); 
     int left = srcMat.width(); 
     int right = 0; 
     int bottom = 0; 

     if(rect.x < left) { 
      left = rect.x; 
     } 
     if(rect.x+rect.width > right){ 
      right = rect.x+rect.width; 
     } 
     if(rect.y < top){ 
      top = rect.y; 
     } 
     if(rect.y+rect.height > bottom){ 
      bottom = rect.y+rect.height; 
     } 

     Point topLeft = new Point(left, top); 
     Point topRight = new Point(right, top); 
     Point bottomRight = new Point(right, bottom); 
     Point bottomLeft = new Point(left, bottom); 

     return warp(srcMat, topLeft, topRight, bottomLeft, bottomRight); 
    } 
    return null; 
} 

Mat warp(Mat inputMat, Point topLeft, Point topRight, Point bottomLeft, Point bottomRight) { 
    int resultWidth = (int)(topRight.x - topLeft.x); 
    int bottomWidth = (int)(bottomRight.x - bottomLeft.x); 
    if(bottomWidth > resultWidth) 
     resultWidth = bottomWidth; 

    int resultHeight = (int)(bottomLeft.y - topLeft.y); 
    int bottomHeight = (int)(bottomRight.y - topRight.y); 
    if (bottomHeight > resultHeight) { 
     resultHeight = bottomHeight; 
    } 

    Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC1); 

    List<Point> source = new ArrayList<>(); 
    source.add(topLeft); 
    source.add(topRight); 
    source.add(bottomLeft); 
    source.add(bottomRight); 
    Mat startM = Converters.vector_Point2f_to_Mat(source); 

    Point ocvPOut1 = new Point(0, 0); 
    Point ocvPOut2 = new Point(resultWidth, 0); 
    Point ocvPOut3 = new Point(0, resultHeight); 
    Point ocvPOut4 = new Point(resultWidth, resultHeight); 
    List<Point> dest = new ArrayList<>(); 
    dest.add(ocvPOut1); 
    dest.add(ocvPOut2); 
    dest.add(ocvPOut3); 
    dest.add(ocvPOut4); 
    Mat endM = Converters.vector_Point2f_to_Mat(dest); 

    Mat perspectiveTransform = Imgproc.getPerspectiveTransform(startM, endM); 

    Imgproc.warpPerspective(inputMat, outputMat, perspectiveTransform, new Size(resultWidth, resultHeight)); 
    return outputMat; 
} 

更新1

替换此:

 return warp(srcMat, topLeft, topRight, bottomLeft, bottomRight); 

这一点:

 return warp(srcMat, topLeft, topRight, bottomRight, bottomLeft); 

结果更新1:

Result Now

更新2

public Mat warp(Mat inputMat, MatOfPoint selectedContour) { 
    MatOfPoint2f new_mat = new MatOfPoint2f(selectedContour.toArray()); 
    MatOfPoint2f approxCurve_temp = new MatOfPoint2f(); 
    int contourSize = (int) selectedContour.total(); 
    Imgproc.approxPolyDP(new_mat, approxCurve_temp, contourSize * 0.05, true); 

    double[] temp_double; 
    temp_double = approxCurve_temp.get(0,0); 
    Point p1 = new Point(temp_double[0], temp_double[1]); 
    temp_double = approxCurve_temp.get(1,0); 
    Point p2 = new Point(temp_double[0], temp_double[1]); 
    temp_double = approxCurve_temp.get(2,0); 
    Point p3 = new Point(temp_double[0], temp_double[1]); 
    temp_double = approxCurve_temp.get(3,0); 
    Point p4 = new Point(temp_double[0], temp_double[1]); 
    List<Point> source = new ArrayList<Point>(); 
    source.add(p1); 
    source.add(p2); 
    source.add(p3); 
    source.add(p4); 
    Mat startM = Converters.vector_Point2f_to_Mat(source); 

    int resultWidth = 846; 
    int resultHeight = 2048; 

    Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC4); 

    Point ocvPOut1 = new Point(0, 0); 
    Point ocvPOut2 = new Point(0, resultHeight); 
    Point ocvPOut3 = new Point(resultWidth, resultHeight); 
    Point ocvPOut4 = new Point(resultWidth, 0); 
    List<Point> dest = new ArrayList<Point>(); 
    dest.add(ocvPOut1); 
    dest.add(ocvPOut2); 
    dest.add(ocvPOut3); 
    dest.add(ocvPOut4); 
    Mat endM = Converters.vector_Point2f_to_Mat(dest); 

    Mat perspectiveTransform = Imgproc.getPerspectiveTransform(startM, endM); 

    Imgproc.warpPerspective(inputMat, outputMat, perspectiveTransform, new Size(resultWidth, resultHeight), 
      Imgproc.INTER_CUBIC); 
    return outputMat; 
} 

结果更新2:

我已经改变了我的经功能的位和代码附加。 然而,合成图像以某种方式在错误的方向上旋转。你能指导我这是做这件事的正确方法吗?

Android设备方向设置为:纵向,输入图像也是纵向。

result_update_2

更新3

我设法通过排序的角落,像这样伸直令牌:

List<Point> source = new ArrayList<Point>(); 
    source.add(p2); 
    source.add(p3); 
    source.add(p4); 
    source.add(p1); 
    Mat startM = Converters.vector_Point2f_to_Mat(source); 

结果更新3:

Result Update 3

然而,由此产生的图像从左侧裁剪,我不知道如何解决这个问题。 如果令牌向右或向左倾斜并且输出图像是笔直的,我已设法拉直输入图像。但是,如果输入图像已经将令牌居中且直线向上。它旋转像这样的令牌,使用相同的代码:

问题更新3:

Issue Update 3

回答

1

到纠偏票转型是接近仿射之一。您可以通过用平行四边形近似轮廓来获得它。您可以将平行四边形的顶点作为最左边,最顶端,最右边和最底部的点。其实,你只需要三个顶点(第四个可以从这些顶点重新计算)。也许平行四边形的最小二乘拟合是可能的,我不知道。

另一种选择是考虑从四个点定义的单应变换(但计算更复杂)。它将考虑到视角。 (您可能会在这里获得一些见解:https://www.codeproject.com/Articles/674433/Perspective-Projection-of-a-Rectangle-Homography。)

要整理图像,只需应用逆变换并检索矩形即可。无论如何,你会注意到这个矩形的大小是未知的,所以你可以任意缩放它。最难的问题是找到合适的宽高比。

+0

我以为'warpPerception'用于我想在这里实现的目的。我确实有一个轮廓包裹了我想要纠正的标记区域,我是否无法从我已经过滤的轮廓中找到角落?你能否看看我发布的代码,并分享这个错误,因为它只是裁剪基于轮廓拐角的主图像,而不是拉直它。 –

+0

@MohsinFalak“我不能从我已经过滤的轮廓中找到角落吗?”:你真的看过我的帖子吗? –

+0

我对于成为一名业余人士表示歉意,但我对OpenCV感到新鲜,并且您的帮助正在一步一步地引起人们的期待。我已经在这个问题上取得了一些进展,问题得到了更新。你能看看并帮我解决这个问题吗? –