List of usage examples for org.opencv.core Scalar Scalar
public Scalar(double[] vals)
From source file:MainTextWatermark.java
public static void main(String[] args) { try {// www. ja va 2s. c o m System.loadLibrary(Core.NATIVE_LIBRARY_NAME); Mat source = Highgui.imread("D://teste.png", Highgui.CV_LOAD_IMAGE_COLOR); Mat destination = new Mat(source.rows(), source.cols(), source.type()); Core.putText(source, "Tutorialspoint.com by DAC", new Point(source.rows() / 2, (source.cols() / 15 * 11)), //Posio do texto na tela Core.FONT_HERSHEY_PLAIN, new Double(1.1), new Scalar(150)); Highgui.imwrite("D://Watermarked.jpg", source); } catch (Exception e) { System.out.println("Exception:" + e.getMessage()); } }
From source file:angryhexclient.OurVision.java
License:Open Source License
/** * Detects the ground in the image./*from w w w . j a v a2 s . c om*/ * @return A list of blocks representing the ground. */ public List<Block> detectGround() { Mat binaryImage = new Mat(new Size(_nWidth, _nHeight), CvType.CV_8U, new Scalar(1)); // We only detect right of this margin. The slingshot has some ground // colors and would partly be detected as ground. This is not what we // want. Trajectories originate at the slingshot, and if there is ground // detected at the slingshot, the agent will think, that none of its // trajectories are valid. Therefore we start with detecting due right // of the slingshot. int startAtX = findSlingshot().x + findSlingshot().width * 2; // Now we create a binary image of the ground areas. White where there // is ground, black otherwise. for (int y = 0; y < _nHeight; y++) { for (int x = 0; x < _nWidth; x++) { if (x > startAtX && isGround(x, y)) binaryImage.put(y, x, 255); else binaryImage.put(y, x, 0); } } Mat smoothedImage = new Mat(new Size(_nWidth, _nHeight), CvType.CV_8U, new Scalar(1)); // This median filter improves the detection tremendously. There are a // whole lot of single pixels that carry ground colors spread all over // the image. We remove them here. Imgproc.medianBlur(binaryImage, smoothedImage, 7); List<MatOfPoint> contours = new ArrayList<MatOfPoint>(); // We use OpenCV to find the contours. Contours are lines, that // represent the boundaries of the objects in the binary image. Imgproc.findContours(smoothedImage, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); ArrayList<Block> result = new ArrayList<Block>(); //Now for every contour, we convert it to blocks for communicating them to DLV. for (MatOfPoint mp : contours) { org.opencv.core.Point[] pts = mp.toArray(); for (int i = 0; i < pts.length - 1; i++) { Block b = new Block((int) pts[i].x, (int) pts[i].y); b.add((int) pts[i + 1].x, (int) pts[i + 1].y); result.add(b); } //One block for the first vertex to the last vertex. Block b = new Block((int) pts[pts.length - 1].x, (int) pts[pts.length - 1].y); b.add((int) pts[0].x, (int) pts[0].y); result.add(b); } return result; }
From source file:arlocros.ArMarkerPoseEstimator.java
License:Apache License
private void start(final ConnectedNode connectedNode) { // load OpenCV shared library System.loadLibrary(Core.NATIVE_LIBRARY_NAME); // read configuration variables from the ROS Runtime (configured in the // launch file) log = connectedNode.getLog();/* www . ja v a 2 s.co m*/ // Read Marker Config markerConfig = MarkerConfig.createFromConfig(parameter.markerConfigFile(), parameter.patternDirectory()); camp = getCameraInfo(connectedNode, parameter); // start to listen to transform messages in /tf in order to feed the // Transformer and lookup transforms final TransformationService transformationService = TransformationService.create(connectedNode); // Subscribe to Image Subscriber<sensor_msgs.Image> subscriberToImage = connectedNode.newSubscriber(parameter.cameraImageTopic(), sensor_msgs.Image._TYPE); ComputePose computePose = null; try { final Mat cameraMatrix = CameraParams.getCameraMatrix(camp); final MatOfDouble distCoeffs = CameraParams.getDistCoeffs(camp); computePose = ComputePose.create(markerConfig, new Size(camp.width(), camp.height()), cameraMatrix, distCoeffs, this.parameter.visualization()); } catch (NyARException e) { logger.info("Cannot initialize ComputePose", e); } catch (FileNotFoundException e) { logger.info("Cannot find file when initialize ComputePose", e); } final ComputePose poseProcessor = computePose; final Publisher<tf2_msgs.TFMessage> tfPublisherCamToMarker = connectedNode.newPublisher("tf", tf2_msgs.TFMessage._TYPE); final Publisher<tf2_msgs.TFMessage> tfPublisherMapToOdom = connectedNode.newPublisher("tf", tf2_msgs.TFMessage._TYPE); logger.info("My instance id is " + parameter.instanceId()); if (heartbeatMonitor != null) { logger.info("Start waiting for arlocros id: " + (parameter.instanceId() - 1)); while (true) { final Time currentTime = connectedNode.getCurrentTime(); final Time lastHeartbeatTime = heartbeatMonitor.getLastTimeReceivedMessage(); if (lastHeartbeatTime != null) { final Duration duration = currentTime.subtract(lastHeartbeatTime); if (duration.totalNsecs() > 3.0E8) { logger.info("Not received any heartbeat for 300ms. Start running."); break; } } } } subscriberToImage.addMessageListener(new MessageListener<sensor_msgs.Image>() { @Override public void onNewMessage(sensor_msgs.Image message) { // if (!message.getEncoding().toLowerCase().equals("rgb8")) { log.error("Sorry, " + message.getEncoding() + " Image encoding is not supported! EXITING"); System.exit(-1); } if (camp != null) { try { // final Mat image = Utils.matFromImage(message); // uncomment to add more contrast to the image final Mat thresholdedImage = Utils.tresholdContrastBlackWhite(image, parameter.filterBlockSize(), parameter.subtractedConstant(), parameter.invertBlackWhiteColor()); image.release(); // Mat cannyimg = new Mat(image.height(), image.width(), // CvType.CV_8UC3); // Imgproc.Canny(image, cannyimg, 10, 100); // Imshow.show(cannyimg); // image.convertTo(image, -1, 1.5, 0); // setup camera matrix and return vectors // compute pose final Mat rvec = new Mat(3, 1, CvType.CV_64F); final MatOfDouble tvec = new MatOfDouble(1.0, 1.0, 1.0); final boolean hasPose = poseProcessor.computePose(rvec, tvec, thresholdedImage); if (!hasPose) { return; } thresholdedImage.release(); // publish pose final QuaternionHelper q = new QuaternionHelper(); // convert rotation vector result of solvepnp to rotation matrix Mat R = new Mat(3, 3, CvType.CV_32FC1); Calib3d.Rodrigues(rvec, R); // see publishers before for documentation final Mat tvec_map_cam = new MatOfDouble(1.0, 1.0, 1.0); R = R.t(); final double bankX = Math.atan2(-R.get(1, 2)[0], R.get(1, 1)[0]); final double headingY = Math.atan2(-R.get(2, 0)[0], R.get(0, 0)[0]); final double attitudeZ = Math.asin(R.get(1, 0)[0]); q.setFromEuler(bankX, headingY, attitudeZ); Core.multiply(R, new Scalar(-1), R); Core.gemm(R, tvec, 1, new Mat(), 0, tvec_map_cam, 0); R.release(); final org.ros.rosjava_geometry.Quaternion rotation = new org.ros.rosjava_geometry.Quaternion( q.getX(), q.getY(), q.getZ(), q.getW()); final double x = tvec_map_cam.get(0, 0)[0]; final double y = tvec_map_cam.get(1, 0)[0]; final double z = tvec_map_cam.get(2, 0)[0]; tvec_map_cam.release(); final org.ros.rosjava_geometry.Vector3 translation = new org.ros.rosjava_geometry.Vector3(x, y, z); final org.ros.rosjava_geometry.Transform transform_map_cam = new org.ros.rosjava_geometry.Transform( translation, rotation); // odom to camera_rgb_optical_frame final GraphName sourceFrame = GraphName.of(parameter.cameraFrameName()); final GraphName targetFrame = GraphName.of("base_link"); org.ros.rosjava_geometry.Transform transform_cam_base = null; if (transformationService.canTransform(targetFrame, sourceFrame)) { try { transform_cam_base = transformationService.lookupTransform(targetFrame, sourceFrame); } catch (Exception e) { log.error(ExceptionUtils.getStackTrace(e)); log.info("Cloud not get transformation from " + parameter.cameraFrameName() + " to " + "base_link! " + "However, will continue.."); // cancel this loop..no result can be computed return; } } else { log.info("Cloud not get transformation from " + parameter.cameraFrameName() + " to " + "base_link!" + " However, " + "will continue.."); // cancel this loop..no result can be computed return; } // multiply results org.ros.rosjava_geometry.Transform current_pose = org.ros.rosjava_geometry.Transform .identity(); current_pose = current_pose.multiply(transform_map_cam); current_pose = current_pose.multiply(transform_cam_base); if (current_pose.getTranslation().getZ() < 0.5) { return; } // check for plausibility of the pose by checking if movement // exceeds max speed (defined) of the robot if (parameter.badPoseReject()) { Time current_timestamp = connectedNode.getCurrentTime(); // TODO Unfortunately, we do not have the tf timestamp at // hand here. So we can only use the current timestamp. double maxspeed = 5; boolean goodpose = false; // if (current_pose != null && current_timestamp != null) { if ((last_pose != null && last_timestamp != null) && !Double.isNaN(last_pose.getTranslation().getX())) { // check speed of movement between last and current pose double distance = PoseCompare.distance(current_pose, last_pose); double timedelta = PoseCompare.timedelta(current_timestamp, last_timestamp); if ((distance / timedelta) < maxspeed) { if (smoothing) { double xold = last_pose.getTranslation().getX(); double yold = last_pose.getTranslation().getY(); double zold = last_pose.getTranslation().getZ(); double xnew = current_pose.getTranslation().getX(); double ynew = current_pose.getTranslation().getY(); double znew = current_pose.getTranslation().getZ(); final org.ros.rosjava_geometry.Vector3 smoothTranslation = new org.ros.rosjava_geometry.Vector3( (xold * 2 + xnew) / 3, (yold * 2 + ynew) / 3, (zold * 2 + znew) / 3); current_pose = new org.ros.rosjava_geometry.Transform(smoothTranslation, current_pose.getRotationAndScale()); last_pose = current_pose; } last_pose = current_pose; last_timestamp = current_timestamp; goodpose = true; } else { log.info("distance " + distance + " time: " + timedelta + " --> Pose rejected"); log.info("current pose: " + current_pose.getTranslation().getX() + " " + current_pose.getTranslation().getY() + " " + current_pose.getTranslation().getZ()); log.info("last pose: " + last_pose.getTranslation().getX() + " " + last_pose.getTranslation().getY() + " " + last_pose.getTranslation().getZ()); } } else { last_pose = current_pose; last_timestamp = current_timestamp; } // } // bad pose rejection if (!goodpose) { return; } } // set information to message final geometry_msgs.PoseStamped posestamped = posePublisher.newMessage(); Pose pose = posestamped.getPose(); Quaternion orientation = pose.getOrientation(); Point point = pose.getPosition(); point.setX(current_pose.getTranslation().getX()); point.setY(current_pose.getTranslation().getY()); point.setZ(current_pose.getTranslation().getZ()); orientation.setW(current_pose.getRotationAndScale().getW()); orientation.setX(current_pose.getRotationAndScale().getX()); orientation.setY(current_pose.getRotationAndScale().getY()); orientation.setZ(current_pose.getRotationAndScale().getZ()); // frame_id too posestamped.getHeader().setFrameId("map"); posestamped.getHeader().setStamp(connectedNode.getCurrentTime()); posePublisher.publish(posestamped); mostRecentPose.set(posestamped); // publishCamFrameToMarkerFrame(rvec, tvec, tfPublisherCamToMarker, connectedNode); // publishMapToOdom( // rvec, tvec, transformationService, tfPublisherMapToOdom, connectedNode); rvec.release(); tvec.release(); } catch (Exception e) { logger.info("An exception occurs.", e); } } } }); }
From source file:arlocros.ArMarkerPoseEstimator.java
License:Apache License
private void publishMapToOdom(Mat rvec, Mat tvec, TransformationService transformationService, Publisher<tf2_msgs.TFMessage> tfPublisherMapToOdom, ConnectedNode connectedNode) { // compute transform map to odom from map to // camera_rgb_optical_frame and odom to camera_rgb_optical_frame // map to camera_rgb_optical_frame Mat tvec_map_cam = new MatOfDouble(1.0, 1.0, 1.0); QuaternionHelper q = new QuaternionHelper(); // get rotation matrix R from solvepnp output rotation vector // rvec//w ww.j ava2 s . co m Mat R = new Mat(3, 3, CvType.CV_32FC1); Calib3d.Rodrigues(rvec, R); // transpose R, because we need the transformation from // world(map) to camera R = R.t(); // get rotation around X,Y,Z from R in radiants double bankX = Math.atan2(-R.get(1, 2)[0], R.get(1, 1)[0]); double headingY = Math.atan2(-R.get(2, 0)[0], R.get(0, 0)[0]); double attitudeZ = Math.asin(R.get(1, 0)[0]); q.setFromEuler(bankX, headingY, attitudeZ); // compute translation vector from world (map) to cam // tvec_map_cam Core.multiply(R, new Scalar(-1), R); // R=-R Core.gemm(R, tvec, 1, new Mat(), 0, tvec_map_cam, 0); // tvec_map_cam=R*tvec R.release(); org.ros.rosjava_geometry.Quaternion rotation = new org.ros.rosjava_geometry.Quaternion(q.getX(), q.getY(), q.getZ(), q.getW()); double x = tvec_map_cam.get(0, 0)[0]; double y = tvec_map_cam.get(1, 0)[0]; double z = tvec_map_cam.get(2, 0)[0]; tvec_map_cam.release(); // create a Transform Object that hold the transform map to cam org.ros.rosjava_geometry.Vector3 translation = new org.ros.rosjava_geometry.Vector3(x, y, z); org.ros.rosjava_geometry.Transform transform_map_cam = new org.ros.rosjava_geometry.Transform(translation, rotation); // odom to camera_rgb_optical_frame GraphName sourceFrame = GraphName.of(parameter.cameraFrameName()); GraphName targetFrame = GraphName.of("odom"); org.ros.rosjava_geometry.Transform transform_cam_odom = null; if (transformationService.canTransform(targetFrame, sourceFrame)) { try { transform_cam_odom = transformationService.lookupTransform(targetFrame, sourceFrame); } catch (Exception e) { log.error(ExceptionUtils.getStackTrace(e)); log.info("Cloud not get transformation from " + parameter.cameraFrameName() + " to " + "odom! " + "" + "" + "" + "" + "However, " + "will continue.."); return; } } else { log.info("Cloud not get transformation from " + parameter.cameraFrameName() + " to " + "odom! " + "However, will " + "continue.."); // cancel this loop..no result can be computed return; } // multiply results org.ros.rosjava_geometry.Transform result = org.ros.rosjava_geometry.Transform.identity(); result = result.multiply(transform_map_cam); result = result.multiply(transform_cam_odom); // set information to ROS message TFMessage tfMessage = tfPublisherMapToOdom.newMessage(); TransformStamped transformStamped = connectedNode.getTopicMessageFactory() .newFromType(geometry_msgs.TransformStamped._TYPE); Transform transform = transformStamped.getTransform(); Quaternion orientation = transform.getRotation(); Vector3 vector = transform.getTranslation(); vector.setX(result.getTranslation().getX()); vector.setY(result.getTranslation().getY()); vector.setZ(result.getTranslation().getZ()); orientation.setW(result.getRotationAndScale().getW()); orientation.setX(result.getRotationAndScale().getX()); orientation.setY(result.getRotationAndScale().getY()); orientation.setZ(result.getRotationAndScale().getZ()); transformStamped.getHeader().setFrameId("map"); transformStamped.setChildFrameId("odom"); transformStamped.getHeader().setStamp(connectedNode.getCurrentTime()); // frame_id too tfMessage.getTransforms().add(transformStamped); tfPublisherMapToOdom.publish(tfMessage); }
From source file:ch.zhaw.facerecognitionlibrary.PreProcessor.PreProcessor.java
License:Open Source License
public void normalize01(Mat norm) { Core.normalize(norm, norm, 0.0, 1.0, Core.NORM_MINMAX, CvType.CV_64FC1); Core.MinMaxLocResult minmax = Core.minMaxLoc(norm); Scalar min = new Scalar(minmax.minVal); Core.subtract(norm, min, norm);/*from w w w. java2s . c om*/ minmax = Core.minMaxLoc(norm); Scalar max = new Scalar(minmax.maxVal); Core.divide(norm, max, norm); }
From source file:classes.BlobsFinder.java
public void findBlobContours() { Mat grayImage = new Mat(); Imgproc.cvtColor(image, grayImage, Imgproc.COLOR_BGR2GRAY); ImageUtils.saveImage(grayImage, outImageName + "_grayImage.png", request); Mat gaussianImage = new Mat(); Imgproc.GaussianBlur(grayImage, gaussianImage, new Size(0, 0), 3); Core.addWeighted(grayImage, 1.5, gaussianImage, -1, 0, gaussianImage); ImageUtils.saveImage(gaussianImage, outImageName + "_gaussianGrayImage.png", request); Mat binaryImage = new Mat(); Imgproc.adaptiveThreshold(gaussianImage, binaryImage, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY_INV, 15, 4); ImageUtils.saveImage(binaryImage, outImageName + "_binaryImage.png", request); Mat erodedImage = new Mat(); binaryImage.copyTo(erodedImage);/*from w w w. ja v a2s . c o m*/ Mat structuringElement = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3)); Point anchor = new Point(-1, -1); Imgproc.morphologyEx(erodedImage, erodedImage, Imgproc.MORPH_CLOSE, structuringElement, anchor, 1); ImageUtils.saveImage(erodedImage, outImageName + "_erodedImage.png", request); List<MatOfPoint> contours = new ArrayList<MatOfPoint>(); Imgproc.findContours(erodedImage, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); Mat originalContoursImage = new Mat(image.size(), CvType.CV_8UC1, new Scalar(0)); Scalar contourColor = new Scalar(255); int thickness = -1; // Thicknes should be lower than zero in order to drawn the filled contours Imgproc.drawContours(originalContoursImage, contours, -1, contourColor, thickness); // Drawing all the contours found ImageUtils.saveImage(originalContoursImage, outImageName + "_originalContoursImage.png", request); Mat erodedContoursImage = new Mat(); Imgproc.erode(originalContoursImage, erodedContoursImage, structuringElement, anchor, 1); ImageUtils.saveImage(erodedContoursImage, outImageName + "_erodedContoursImage.png", request); ArrayList<MatOfPoint> finalContours = new ArrayList<MatOfPoint>(); Mat finalContourImage = new Mat(image.size(), CvType.CV_8UC1, new Scalar(0)); Imgproc.findContours(erodedContoursImage, finalContours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); for (int i = 0; i < finalContours.size(); i++) { MatOfPoint currentContour = finalContours.get(i); double area = Imgproc.contourArea(currentContour); if (area > MIN_AREA) { validContours.add(currentContour); String fabricPath = generateFabricPathString(currentContour); contourPaths.add(fabricPath); Rect boundingRect = Imgproc.boundingRect(currentContour); topLeftCorners.add(boundingRect.tl()); contoursAreas.add(area); } } // Drawing ALL the valid contours Imgproc.drawContours(finalContourImage, validContours, -1, contourColor, thickness); ImageUtils.saveImage(finalContourImage, outImageName + "_finalContourImage.png", request); }
From source file:classes.ObjectFinder.java
private void applyMorphologicalFilters() { Mat element = new Mat(3, 3, CvType.CV_8U, new Scalar(1)); Imgproc.erode(thresholdedBackprojection, morphologicalImage, element); Imgproc.morphologyEx(morphologicalImage, morphologicalImage, Imgproc.MORPH_CLOSE, element, new Point(-1, -1), 2); Imgproc.morphologyEx(morphologicalImage, morphologicalImage, Imgproc.MORPH_OPEN, element, new Point(-1, -1), 2);//from w w w. ja va 2s . c om }
From source file:classes.ObjectFinder.java
private void computeSearchWindow() { List<MatOfPoint> contours = new ArrayList<MatOfPoint>(); // a vector of contours // retrieve the external contours // all pixels of each contours Imgproc.findContours(this.morphologicalImage.clone(), contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);//from w w w. j a v a2 s.co m // Draw black contours on a white image this.contoursImage = new Mat(morphologicalImage.size(), CvType.CV_8U, new Scalar(255)); if (contours.size() > 1) { int minContourWith = 20; int minContourHeight = 20; int maxContourWith = 6400 / 2; int maxContourHeight = 4800 / 2; contours = filterContours(contours, minContourWith, minContourHeight, maxContourWith, maxContourHeight); } if (contours.size() > 1) { Collections.sort(contours, new ContourComparator()); // Sorttig the contours to take ONLY the bigger one } computedSearchWindow = new Rect(); massCenter = new Point(-1, -1); if (contours.size() > 0) { this.firstContour = contours.get(0); Mat contournedImage = this.firstContour; // draw all contours in black with a thickness of 2 Scalar color = new Scalar(0); int thickness = 2; Imgproc.drawContours(contoursImage, contours, 0, color, thickness); // // testing the bounding box computedSearchWindow = Imgproc.boundingRect(this.firstContour); topLeftCorner = computedSearchWindow.tl(); // compute all moments Moments mom = Imgproc.moments(contournedImage); massCenter = new Point(mom.get_m10() / mom.get_m00(), mom.get_m01() / mom.get_m00()); // draw black dot Core.circle(contoursImage, massCenter, 4, color, 8); } }
From source file:classes.TextExtractor.java
public void extractText(Rect roi, double roiAngle) throws Exception { Point roiTopLeft = roi.tl();//from w w w .ja v a 2 s. com double radians = Math.toRadians(roiAngle); 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); int[] newWidthHeight = { newWidth, newHeight }; int pivotX = newWidthHeight[0] / 2; int pivotY = newWidthHeight[1] / 2; Point center = new Point(pivotX, pivotY); Size targetSize = new Size(newWidthHeight[0], newWidthHeight[1]); Mat intermediateImage = new Mat(targetSize, image.type()); int offsetX = (newWidthHeight[0] - image.width()) / 2; int offsetY = (newWidthHeight[1] - image.height()) / 2; Point paddedTopLeft = new Point(roiTopLeft.x + offsetX, roiTopLeft.y + offsetY); Mat containerImage = intermediateImage.submat(offsetY, offsetY + image.height(), offsetX, offsetX + image.width()); image.copyTo(containerImage); Mat rotationMatrix = Imgproc.getRotationMatrix2D(center, roiAngle, 1.0); Point transformedTopLeft = transformPoint(paddedTopLeft, rotationMatrix); Mat rotatedImage = new Mat(); Imgproc.warpAffine(intermediateImage, rotatedImage, rotationMatrix, targetSize, Imgproc.INTER_LINEAR, Imgproc.BORDER_CONSTANT, new Scalar(0)); ImageUtils.saveImage(rotatedImage, imageID + "_rotatedImage.png", request); double adjustedWidth = roi.size().width; double adjustedHeight = roi.size().height; if (transformedTopLeft.x + adjustedWidth > rotatedImage.width()) { adjustedWidth = rotatedImage.width() - transformedTopLeft.x; } if (transformedTopLeft.y + adjustedHeight > rotatedImage.height()) { adjustedHeight = rotatedImage.height() - transformedTopLeft.y; } Rect newROI = new Rect(transformedTopLeft, new Size(adjustedWidth, adjustedHeight)); Mat extractedROI = new Mat(rotatedImage, newROI); String fileName = ImageUtils.saveImage(extractedROI, imageID + "_ROI.png", request); extractText(fileName); }
From source file:cmib_4_4.Countour.java
public static void main(String args[]) { System.loadLibrary(Core.NATIVE_LIBRARY_NAME); Mat image = Highgui.imread("input1.jpg", Highgui.CV_LOAD_IMAGE_GRAYSCALE); Mat image1 = Highgui.imread("input1.jpg", Highgui.CV_LOAD_IMAGE_GRAYSCALE); Mat image4 = Highgui.imread("input1.jpg"); Imgproc.threshold(image1, image1, 0, 255, THRESH_OTSU); Imgproc.Canny(image1, image1, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU); Mat image2 = Mat.zeros(image.rows() + 2, image.cols() + 2, CV_8U); List<MatOfPoint> contours = new ArrayList<MatOfPoint>(); Imgproc.findContours(image1, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE); for (int i = 0; i < contours.size(); i++) { if (Imgproc.contourArea(contours.get(i)) > 100) { Rect rect = Imgproc.boundingRect(contours.get(i)); Imgproc.floodFill(image1, image2, new Point(150, 150), new Scalar(255)); Rect rectCrop = new Rect(rect.x, rect.y, rect.width, rect.height); Mat image_roi_rgb = new Mat(image4, rectCrop); Highgui.imwrite("crop2.jpg", image_roi_rgb); if (rect.height > 28) { Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 0, 255)); }/*from w ww .j ava 2s.c om*/ } } Highgui.imwrite("falciparum2.jpg", image); }