android opencv optical mark recognition [closed]

asked 2020-07-08 12:36:02 -0500

ch gravatar image

updated 2020-07-08 14:39:09 -0500

supra56 gravatar image

I want to use opencv for OMR sheet or Bubble sheet .I dont have fix number of questions or columns in my omr sheet so i am trying to detetct rows and column (also i need to detect the title of the column)and then i can move further for filled circle detetction. I get crash on lineImgproc.boundingRect(contours[i]) .ALso i checked the intermediate result i get the row and column image ,not perfect though

P.S I am very new to opencv my approach may be incorrect ,I would be thankful for any advice.I have a similar omr sheet as in image number of questions and number of column is not fixed ,I need to identify number od=f column,number of question, column title,filled circle i.e answer so i try to detetct the lines (horizontal and vertical).

image description

fun showAllBorders(paramView: Bitmap?) { //   paramView = BitmapFactory.decodeFile(filename.getPath());
    localMat1 = Mat()
    var scale = 25.0
   var contourNo:Int=0
    Utils.bitmapToMat(paramView, localMat1)
    localMat1 = Mat()

    var thresMat = Mat()

    var horiMat = Mat()
    var grayMat = Mat()
    var vertMat = Mat()
    Utils.bitmapToMat(paramView, localMat1)
    val imgSource: Mat = localMat1.clone()

     Imgproc.cvtColor(imgSource, grayMat, Imgproc.COLOR_RGB2GRAY)

    Imgproc.adaptiveThreshold(grayMat, thresMat, 255.0, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, 15, -2.0)


    horiMat = thresMat.clone()
    vertMat = thresMat.clone()

    val horizontalSize1 = horiMat.cols().toDouble() / scale
    val horizontalStructure: Mat = Imgproc.getStructuringElement(MORPH_RECT, Size(horizontalSize1, 1.0))

    Imgproc.erode(horiMat, horiMat, horizontalStructure, Point(-1.0, -1.0), 1)
    Imgproc.dilate(horiMat, horiMat, horizontalStructure, Point(-1.0, -1.0), 1)




    val verticalSize1 = vertMat.rows().toDouble() //scale
    val verticalStructure: Mat = Imgproc.getStructuringElement(MORPH_RECT, Size(1.0, verticalSize1))

    Imgproc.erode(vertMat, vertMat, verticalStructure, Point(-1.0, -1.0), 1)
    Imgproc.dilate(vertMat, vertMat, verticalStructure, Point(-1.0, -1.0), 4)

    var mask: Mat = Mat()
    var resultMat: Mat = Mat()
    Core.add(horiMat, vertMat, resultMat)


    var jointsMat: Mat = Mat()
    Core.bitwise_and(horiMat, vertMat, jointsMat)


    val contours: List<MatOfPoint> = ArrayList()
    val cnts: List<MatOfPoint> = ArrayList()
    val hierarchy = Mat()
    var rect: Rect? = null
    var rois = mutableListOf<Mat>()
    var bmpList = mutableListOf<Bitmap>()


    Imgproc.findContours(resultMat, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE)

    for (i in contours.indices) {

        if (Imgproc.contourArea(contours[i]) < 100) {


            contourNo = i

            val contour2f = MatOfPoint2f(*contours[contourNo].toArray())
            val contours_poly = MatOfPoint2f(*contours[contourNo].toArray())

            Imgproc.approxPolyDP(contour2f, contours_poly, 3.0, true)
            val points = MatOfPoint(*contours_poly.toArray())
            var boundRect = mutableListOf<Rect>()

            boundRect[i] = Imgproc.boundingRect(contours[i]);//CRASH HERE//contours[i] is not null 


            val roi = Mat(jointsMat, boundRect[i])


            val joints_contours: List<MatOfPoint> = ArrayList()

            val hierarchy1 = Mat()



            Imgproc.findContours(roi, joints_contours, hierarchy1, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE)

            if (joints_contours.size >= 4) {

                rois.add(Mat(jointsMat, boundRect[i]))

                Imgproc.cvtColor(localMat1, localMat1, Imgproc.COLOR_GRAY2RGBA);

                Imgproc.drawContours(localMat1, contours, i, Scalar(0.0, 0.0, 255.0), 6);
                rectangle(localMat1, boundRect[i].tl(), boundRect[i].br(), Scalar(0.0, 255.0, 0.0), 1, 8, 0);
            }
        }
    }


    for (i in rois) {

        val analyzed = Bitmap.createBitmap(i.cols(), i.rows(), Bitmap.Config.ARGB_8888)
        Utils.matToBitmap(i, analyzed)
        bmpList.add(analyzed)

    }


    val analyzed = Bitmap.createBitmap(jointsMat.cols(), jointsMat.rows(), Bitmap.Config.ARGB_8888 ...
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Closed for the following reason question is not relevant or outdated by sturkmen
close date 2020-10-27 09:32:48.469169