/**
* Process the given Mat, finding, classifying and displaying all resistors present.
*
* @param originalImg The image to parse
*/
private void parseImage(Mat originalImg) {
Mat workingCopy = new Mat();
originalImg.copyTo(workingCopy);
// blur the original image to form resistor blobs. should remove white/silver/grey bands which
// would otherwise
// get picked up as part of the background, leads or shadows.
Mat blurred = new Mat();
// Imgproc.medianBlur(workingCopy, blurred, 29);
Imgproc.blur(workingCopy, blurred, new Size(20, 20)); // faster
// get a mask off the background
Mat resistorMask = new Mat();
generateResistorMask(blurred, Imgproc.THRESH_BINARY).copyTo(resistorMask);
// find countours in mask
List<MatOfPoint> contours = getContours(resistorMask, originalImg, true);
// extract resistors in input image
List<Resistor> resistors = extractResistorsFromContours(contours, originalImg, true);
// segment and extract colour bands for each resistor
extractColourBandsAndClassify(resistors, true);
// calculate and display resistance value for each resistor based on classified colour bands
calculateAndDisplayResistanceValues(resistors);
}
/**
* @param image
* @param size
* @return Mat
*/
public static Mat cannyDetection(Mat image, int size) {
Mat grayImage = new Mat();
Mat detectedEdges = new Mat();
// convert to grayscale
Imgproc.cvtColor(image, grayImage, Imgproc.COLOR_BGR2GRAY);
// reduce noise with a 3x3 kernel
Imgproc.blur(grayImage, detectedEdges, new Size(3, 3));
// canny detector, with ratio of lower:upper threshold of 3:1
Imgproc.Canny(detectedEdges, detectedEdges, size, size / 3, 7, false);
return detectedEdges;
}
// OpenCV code
private void modifyImage(String fileName) {
// Create a face detector from the cascade file
CascadeClassifier faceDetector = new CascadeClassifier("haarcascade_frontalface_alt.xml");
Mat image = Highgui.imread(fileName);
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
// Blur each face
for (Rect rect : faceDetections.toArray()) {
Mat faceArea = image.submat(rect);
Imgproc.blur(faceArea, faceArea, new Size(30, 30));
}
// Save the modified image
Highgui.imwrite("edited_" + fileName, image);
}
/**
* @param inputImg
* @param minValue
* @param maxValue
* @return Mat
*/
public static Mat thresholding(Mat inputImg, Integer minValue, Integer maxValue) {
Mat frame = inputImg;
// яскравість
// frame.convertTo(frame , -1, 10d * 33 / 100, 0);
// Imgproc.medianBlur(frame,frame, 17);
// Core.bitwise_not(frame,frame );
// Mat frame = new Mat(image.rows(), image.cols(), image.type());
// frame.convertTo(frame, -1, 10d * 20 / 100, 0);
Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// if (this.inverse.isSelected())
// thresh_type = Imgproc.THRESH_BINARY;
// threshold the image with the average hue value
// System.out.println("size " +frame.size());
hsvImg.create(frame.size(), CvType.CV_8U);
// Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
// double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
// System.out.println(threshValue);
/*
if(threshValue > 40){
maxValue = 160;
}else{
maxValue = 40;
}*/
// Imgproc.threshold(hsvPlanes.get(1), thresholdImg, minValue , maxValue , thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(27, 27));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.threshold(thresholdImg, thresholdImg, minValue, maxValue, Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
Core.bitwise_not(thresholdImg, foreground);
frame.copyTo(foreground, thresholdImg);
///////////////////////////////////////////////////////////////////////////////////////
///
////
return foreground;
/*Mat hsvImg = new Mat();
List<Mat> hsvPlanes = new ArrayList<>();
Mat thresholdImg = new Mat();
int thresh_type = Imgproc.THRESH_BINARY_INV;
// threshold the image with the average hue value
hsvImg.create(inputImg.size(), CvType.CV_8U);
Imgproc.cvtColor(inputImg, hsvImg, Imgproc.COLOR_BGR2HSV);
Core.split(hsvImg, hsvPlanes);
// get the average hue value of the image
double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
Imgproc.threshold(hsvPlanes.get(0), thresholdImg, minValue,
maxValue, thresh_type);
Imgproc.blur(thresholdImg, thresholdImg, new Size(3, 3));
// dilate to fill gaps, erode to smooth edges
Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 3);
Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
Imgproc.threshold(thresholdImg, thresholdImg, minValue,
maxValue, Imgproc.THRESH_BINARY);
// create the new image
Mat foreground = new Mat(inputImg.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
inputImg.copyTo(foreground, thresholdImg);
Core.bitwise_not(foreground,foreground);
return foreground;*/
}