Develop Reference

Opencv4Android grabcut's output image has different colors(brighter colors) than the input image

public class Grabcut extends Activity {
ImageView iv;
Bitmap bitmap;
Canvas canvas;
Scalar color = new Scalar(255, 0, 0, 255);
Point tl, br;
int counter;
Bitmap bitmapResult, bitmapBackground;
Mat dst = new Mat();
final String pathToImage = Environment.getExternalStorageDirectory()+"/gcut.png";
public static final String TAG = "Grabcut demo";
static {
if (!OpenCVLoader.initDebug()) {
// Handle initialization error
}
}
#Override
public void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.grabcut_main);
iv = (ImageView) this.findViewById(R.id.imageView);
Bitmap bitmap = BitmapFactory.decodeResource(getResources(), R.drawable.grabcut);
Log.d(TAG, "bitmap: " + bitmap.getWidth() + "x" + bitmap.getHeight());
bitmap = bitmap.copy(Bitmap.Config.ARGB_8888, true);
Log.d(TAG, "bitmap 8888: " + bitmap.getWidth() + "x" + bitmap.getHeight());
//GrabCut part
Mat img = new Mat();
Utils.bitmapToMat(bitmap, img);
Log.d(TAG, "img: " + img);
int r = img.rows();
int c = img.cols();
Point p1 = new Point(c/5, r/5);
Point p2 = new Point(c-c/5, r-r/8);
Rect rect = new Rect(p1,p2);
//Rect rect = new Rect(50,30, 100,200);
Log.d(TAG, "rect: " + rect);
Mat mask = new Mat();
debugger(""+mask.type());
mask.setTo(new Scalar(125));
Mat fgdModel = new Mat();
fgdModel.setTo(new Scalar(255, 255, 255));
Mat bgdModel = new Mat();
bgdModel.setTo(new Scalar(255, 255, 255));
Mat imgC3 = new Mat();
Imgproc.cvtColor(img, imgC3, Imgproc.COLOR_RGBA2RGB);
Log.d(TAG, "imgC3: " + imgC3);
Log.d(TAG, "Grabcut begins");
Imgproc.grabCut(imgC3, mask, rect, bgdModel, fgdModel, 5, Imgproc.GC_INIT_WITH_RECT);
Mat source = new Mat(1, 1, CvType.CV_8U, new Scalar(3.0));
Core.compare(mask, source, mask, Core.CMP_EQ);
Mat foreground = new Mat(img.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
img.copyTo(foreground, mask);
Core.rectangle(img, p1, p2, color);
Mat background = new Mat();
try {
background = Utils.loadResource(getApplicationContext(),
R.drawable.wall2 );
} catch (IOException e) {
e.printStackTrace();
}
Mat tmp = new Mat();
Imgproc.resize(background, tmp, img.size());
background = tmp;
Mat tempMask = new Mat(foreground.size(), CvType.CV_8UC1, new Scalar(255, 255, 255));
Imgproc.cvtColor(foreground, tempMask, 6/* COLOR_BGR2GRAY */);
//Imgproc.threshold(tempMask, tempMask, 254, 255, 1 /* THRESH_BINARY_INV */);
Mat vals = new Mat(1, 1, CvType.CV_8UC3, new Scalar(0.0));
dst = new Mat();
background.setTo(vals, tempMask);
Imgproc.resize(foreground, tmp, mask.size());
foreground = tmp;
Core.add(background, foreground, dst, tempMask);
//convert to Bitmap
Log.d(TAG, "Convert to Bitmap");
Utils.matToBitmap(dst, bitmap);
iv.setBackgroundResource(R.drawable.wall2);
iv.setImageBitmap(bitmap);
//release MAT part
img.release();
imgC3.release();
mask.release();
fgdModel.release();
bgdModel.release();
}
public void debugger(String s){
Log.v("","########### "+s);
}
}
I had followed above tutorial.But problem is that output image I get has brighter colors than my input image. Why is that and how to solve it?
My input image is Here and output image is here.Output image is actually screenshot of my application where large one is input image and small one with black background is output image.

I finally found solution to my problem. Here is code to grab cut background of an image using Grabcut algorithm in opencv for android.
public void grabcutAlgo(Bitmap bit){
Bitmap b = bit.copy(Bitmap.Config.ARGB_8888, true);
Point tl=new Point();
Point br=new Point();
//GrabCut part
Mat img = new Mat();
Utils.bitmapToMat(b, img);
Imgproc.cvtColor(img, img, Imgproc.COLOR_RGBA2RGB);
int r = img.rows();
int c = img.cols();
Point p1 = new Point(c / 100, r / 100);
Point p2 = new Point(c - c / 100, r - r / 100);
Rect rect = new Rect(p1, p2);
//Rect rect = new Rect(tl, br);
Mat background = new Mat(img.size(), CvType.CV_8UC3,
new Scalar(255, 255, 255));
Mat firstMask = new Mat();
Mat bgModel = new Mat();
Mat fgModel = new Mat();
Mat mask;
Mat source = new Mat(1, 1, CvType.CV_8U, new Scalar(Imgproc.GC_PR_FGD));
Mat dst = new Mat();
Imgproc.grabCut(img, firstMask, rect, bgModel, fgModel, 5, Imgproc.GC_INIT_WITH_RECT);
Core.compare(firstMask, source, firstMask, Core.CMP_EQ);
Mat foreground = new Mat(img.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
img.copyTo(foreground, firstMask);
Scalar color = new Scalar(255, 0, 0, 255);
Imgproc.rectangle(img, tl, br, color);
Mat tmp = new Mat();
Imgproc.resize(background, tmp, img.size());
background = tmp;
mask = new Mat(foreground.size(), CvType.CV_8UC1,
new Scalar(255, 255, 255));
Imgproc.cvtColor(foreground, mask, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(mask, mask, 254, 255, Imgproc.THRESH_BINARY_INV);
System.out.println();
Mat vals = new Mat(1, 1, CvType.CV_8UC3, new Scalar(0.0));
background.copyTo(dst);
background.setTo(vals, mask);
Core.add(background, foreground, dst, mask);
Bitmap grabCutImage = Bitmap.createBitmap(dst.cols(), dst.rows(), Bitmap.Config.ARGB_8888);
Bitmap processedImage = Bitmap.createBitmap(dst.cols(), dst.rows(), Bitmap.Config.RGB_565);
Utils.matToBitmap(dst, grabCutImage);
dst.copyTo(sampleImage);
imageView.setImageBitmap(grabCutImage);
firstMask.release();
source.release();
bgModel.release();
fgModel.release();
}

OpenCV image Comparison And Similarity in Android

I'm OpenCV learner. I was trying Image Comparison. I have used OpenCV 2.4.13.3
I have these two images 1.jpg and cam1.jpg.
When I use the following command in openCV
File sdCard = Environment.getExternalStorageDirectory();
String path1, path2;
path1 = sdCard.getAbsolutePath() + "/1.jpg";
path2 = sdCard.getAbsolutePath() + "/cam1.jpg";
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.BRIEF);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
Mat img1 = Highgui.imread(path1);
Mat img2 = Highgui.imread(path2);
Mat descriptors1 = new Mat();
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
detector.detect(img1, keypoints1);
extractor.compute(img1, keypoints1, descriptors1);
//second image
// Mat img2 = Imgcodecs.imread(path2);
Mat descriptors2 = new Mat();
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
detector.detect(img2, keypoints2);
extractor.compute(img2, keypoints2, descriptors2);
//matcher image descriptors
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1,descriptors2,matches);
// Filter matches by distance
MatOfDMatch filtered = filterMatchesByDistance(matches);
int total = (int) matches.size().height;
int Match= (int) filtered.size().height;
Log.d("LOG", "total:" + total + " Match:"+Match);
Method filterMatchesByDistance
static MatOfDMatch filterMatchesByDistance(MatOfDMatch matches){
List<DMatch> matches_original = matches.toList();
List<DMatch> matches_filtered = new ArrayList<DMatch>();
int DIST_LIMIT = 30;
// Check all the matches distance and if it passes add to list of filtered matches
Log.d("DISTFILTER", "ORG SIZE:" + matches_original.size() + "");
for (int i = 0; i < matches_original.size(); i++) {
DMatch d = matches_original.get(i);
if (Math.abs(d.distance) <= DIST_LIMIT) {
matches_filtered.add(d);
}
}
Log.d("DISTFILTER", "FIL SIZE:" + matches_filtered.size() + "");
MatOfDMatch mat = new MatOfDMatch();
mat.fromList(matches_filtered);
return mat;
}
Log
total:122 Match:30
As we can see from the log match is 30.
But as we can see both images have same visual element (in).
How can I get match=90 using openCV?
It would be great if somebody can help with code snippet.
If using opencv it is not possible then what are the other
alternatives we can look for?

But as we can see both images have same visual element (in).
So, we should compare not whole images, but "same visual element" on it. You can improve Match value more if you do not compare the "template" and "camera" images themselves, but processed same way (converted to binary black/white, for example) "template" and "camera" images. For example, try to find blue (background of template logo) square on both ("template" and "camera") images and compare that squares (Region Of Interest). The code may be something like that:
Bitmap bmImageTemplate = <get your template image Bitmap>;
Bitmap bmTemplate = findLogo(bmImageTemplate); // process template image
Bitmap bmImage = <get your camera image Bitmap>;
Bitmap bmLogo = findLogo(bmImage); // process camera image same way
compareBitmaps(bmTemplate, bmLogo);
where
private Bitmap findLogo(Bitmap sourceBitmap) {
Bitmap roiBitmap = null;
Mat sourceMat = new Mat(sourceBitmap.getWidth(), sourceBitmap.getHeight(), CvType.CV_8UC3);
Utils.bitmapToMat(sourceBitmap, sourceMat);
Mat roiTmp = sourceMat.clone();
final Mat hsvMat = new Mat();
sourceMat.copyTo(hsvMat);
// convert mat to HSV format for Core.inRange()
Imgproc.cvtColor(hsvMat, hsvMat, Imgproc.COLOR_RGB2HSV);
Scalar lowerb = new Scalar(85, 50, 40); // lower color border for BLUE
Scalar upperb = new Scalar(135, 255, 255); // upper color border for BLUE
Core.inRange(hsvMat, lowerb, upperb, roiTmp); // select only blue pixels
// find contours
List<MatOfPoint> contours = new ArrayList<>();
List<Rect> squares = new ArrayList<>();
Imgproc.findContours(roiTmp, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
// find appropriate bounding rectangles
for (MatOfPoint contour : contours) {
MatOfPoint2f areaPoints = new MatOfPoint2f(contour.toArray());
RotatedRect boundingRect = Imgproc.minAreaRect(areaPoints);
double rectangleArea = boundingRect.size.area();
// test min ROI area in pixels
if (rectangleArea > 400) {
Point rotated_rect_points[] = new Point[4];
boundingRect.points(rotated_rect_points);
Rect rect = Imgproc.boundingRect(new MatOfPoint(rotated_rect_points));
double aspectRatio = rect.width > rect.height ?
(double) rect.height / (double) rect.width : (double) rect.width / (double) rect.height;
if (aspectRatio >= 0.9) {
squares.add(rect);
}
}
}
Mat logoMat = extractSquareMat(roiTmp, getBiggestSquare(squares));
roiBitmap = Bitmap.createBitmap(logoMat.cols(), logoMat.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(logoMat, roiBitmap);
return roiBitmap;
}
method extractSquareMat() just extract Region of Interest (logo) from whole image
public static Mat extractSquareMat(Mat sourceMat, Rect rect) {
Mat squareMat = null;
int padding = 50;
if (rect != null) {
Rect truncatedRect = new Rect((int) rect.tl().x + padding, (int) rect.tl().y + padding,
rect.width - 2 * padding, rect.height - 2 * padding);
squareMat = new Mat(sourceMat, truncatedRect);
}
return squareMat ;
}
and compareBitmaps() just wrapper for your code:
private void compareBitmaps(Bitmap bitmap1, Bitmap bitmap2) {
Mat mat1 = new Mat(bitmap1.getWidth(), bitmap1.getHeight(), CvType.CV_8UC3);
Utils.bitmapToMat(bitmap1, mat1);
Mat mat2 = new Mat(bitmap2.getWidth(), bitmap2.getHeight(), CvType.CV_8UC3);
Utils.bitmapToMat(bitmap2, mat2);
compareMats(mat1, mat2);
}
your code as method:
private void compareMats(Mat img1, Mat img2) {
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.BRIEF);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
Mat descriptors1 = new Mat();
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
detector.detect(img1, keypoints1);
extractor.compute(img1, keypoints1, descriptors1);
//second image
// Mat img2 = Imgcodecs.imread(path2);
Mat descriptors2 = new Mat();
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
detector.detect(img2, keypoints2);
extractor.compute(img2, keypoints2, descriptors2);
//matcher image descriptors
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1,descriptors2,matches);
// Filter matches by distance
MatOfDMatch filtered = filterMatchesByDistance(matches);
int total = (int) matches.size().height;
int Match= (int) filtered.size().height;
Log.d("LOG", "total:" + total + " Match:" + Match);
}
static MatOfDMatch filterMatchesByDistance(MatOfDMatch matches){
List<DMatch> matches_original = matches.toList();
List<DMatch> matches_filtered = new ArrayList<DMatch>();
int DIST_LIMIT = 30;
// Check all the matches distance and if it passes add to list of filtered matches
Log.d("DISTFILTER", "ORG SIZE:" + matches_original.size() + "");
for (int i = 0; i < matches_original.size(); i++) {
DMatch d = matches_original.get(i);
if (Math.abs(d.distance) <= DIST_LIMIT) {
matches_filtered.add(d);
}
}
Log.d("DISTFILTER", "FIL SIZE:" + matches_filtered.size() + "");
MatOfDMatch mat = new MatOfDMatch();
mat.fromList(matches_filtered);
return mat;
}
As result for resized (scaled for 50%) images saved from your question result is:
D/DISTFILTER: ORG SIZE:237
D/DISTFILTER: FIL SIZE:230
D/LOG: total:237 Match:230
NB! This is a quick and dirty example just to demonstrate approach only for given template.
P.S. getBiggestSquare() can be like that (based on compare by area):
public static Rect getBiggestSquare(List<Rect> squares) {
Rect biggestSquare = null;
if (squares != null && squares.size() >= 1) {
Rect square;
double maxArea;
int ixMaxArea = 0;
square = squares.get(ixMaxArea);
maxArea = square.area();
for (int ix = 1; ix < squares.size(); ix++) {
square = squares.get(ix);
if (square.area() > maxArea) {
maxArea = square.area();
ixMaxArea = ix;
}
}
biggestSquare = squares.get(ixMaxArea);
}
return biggestSquare;
}

How to detect marked black regions inside largest Rectangle Contour?

I can detect largest contour the answer sheet (20 questions, each have 4 alternative)
After the draw largest contour, what shall I do? Divide matris the rectangle by 20x4 cell? Or find countour again but this time inside the rectangle? I dont know what I need. Just I want to get which is marked.
I looked at this documant.
How to codding "image gridding and division"?
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
return findLargestRectangle(inputFrame.rgba());
}
private Mat findLargestRectangle(Mat original_image) {
Mat imgSource = original_image;
hierarchy = new Mat();
//convert the image to black and white
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);
//convert the image to black and white does (8 bit)
Imgproc.Canny(imgSource, imgSource, 50, 50);
//apply gaussian blur to smoothen lines of dots
Imgproc.GaussianBlur(imgSource, imgSource, new Size(5, 5), 5);
//find the contours
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(imgSource, contours, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
hierarchy.release();
double maxArea = -1;
int maxAreaIdx = -1;
MatOfPoint temp_contour = contours.get(0); //the largest is at the index 0 for starting point
MatOfPoint2f approxCurve = new MatOfPoint2f();
Mat largest_contour = contours.get(0);
List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
for (int idx = 0; idx < contours.size(); idx++) {
temp_contour = contours.get(idx);
double contourarea = Imgproc.contourArea(temp_contour);
//compare this contour to the previous largest contour found
if (contourarea > maxArea) {
//check if this contour is a square
MatOfPoint2f new_mat = new MatOfPoint2f( temp_contour.toArray() );
int contourSize = (int)temp_contour.total();
Imgproc.approxPolyDP(new_mat, approxCurve, contourSize*0.05, true);
if (approxCurve.total() == 4) {
maxArea = contourarea;
maxAreaIdx = idx;
largest_contours.add(temp_contour);
largest_contour = temp_contour;
}
}
}
MatOfPoint temp_largest = largest_contours.get(largest_contours.size()-1);
largest_contours = new ArrayList<MatOfPoint>();
largest_contours.add(temp_largest);
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BayerBG2RGB);
Imgproc.drawContours(imgSource, contours, maxAreaIdx, new Scalar(0, 255, 0), 1);
Log.d(TAG, "Largers Contour:" + contours.get(maxAreaIdx).toString());
return imgSource;
}
UPDATE 1:
I want to thank you #sturkmen for the his answer. I can read and find black regions now. Here the Android codes:
public View onCreateView(LayoutInflater inflater, ViewGroup container,
Bundle savedInstanceState) {
View _view = inflater.inflate(R.layout.fragment_main, container, false);
// Inflate the layout for this fragment
Button btnTest = (Button) _view.findViewById(R.id.btnTest);
btnTest.setOnClickListener(new View.OnClickListener() {
#Override
public void onClick(View v) {
Mat img = Imgcodecs.imread(mediaStorageDir().getPath() + "/" + "test2.jpg");
if (img.empty()) {
Log.d("Fragment", "IMG EMPTY");
}
Mat gray = new Mat();
Mat thresh = new Mat();
//convert the image to black and white
Imgproc.cvtColor(img, gray, Imgproc.COLOR_BGR2GRAY);
//convert the image to black and white does (8 bit)
Imgproc.threshold(gray, thresh, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU);
Mat temp = thresh.clone();
//find the contours
Mat hierarchy = new Mat();
Mat corners = new Mat(4,1, CvType.CV_32FC2);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(temp, contours,hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
hierarchy.release();
for (int idx = 0; idx < contours.size(); idx++)
{
MatOfPoint contour = contours.get(idx);
MatOfPoint2f contour_points = new MatOfPoint2f(contour.toArray());
RotatedRect minRect = Imgproc.minAreaRect( contour_points );
Point[] rect_points = new Point[4];
minRect.points( rect_points );
if(minRect.size.height > img.width() / 2)
{
List<Point> srcPoints = new ArrayList<Point>(4);
srcPoints.add(rect_points[2]);
srcPoints.add(rect_points[3]);
srcPoints.add(rect_points[0]);
srcPoints.add(rect_points[1]);
corners = Converters.vector_Point_to_Mat(
srcPoints, CvType.CV_32F);
}
}
Imgproc.erode(thresh, thresh, new Mat(), new Point(-1,-1), 10);
Imgproc.dilate(thresh, thresh, new Mat(), new Point(-1,-1), 5);
Mat results = new Mat(1000,250,CvType.CV_8UC3);
Mat quad = new Mat(1000,250,CvType.CV_8UC1);
List<Point> dstPoints = new ArrayList<Point>(4);
dstPoints.add(new Point(0, 0));
dstPoints.add(new Point(1000, 0));
dstPoints.add(new Point(1000, 250));
dstPoints.add(new Point(0, 250));
Mat quad_pts = Converters.vector_Point_to_Mat(
dstPoints, CvType.CV_32F);
Mat transmtx = Imgproc.getPerspectiveTransform(corners, quad_pts);
Imgproc.warpPerspective( img, results, transmtx, new Size(1000,250));
Imgproc.warpPerspective( thresh, quad, transmtx, new Size(1000,250));
Imgproc.resize(quad,quad,new Size(20,5));
Imgcodecs.imwrite("results.png",quad);
//show image
showImage(quad);
//store image
storeImage(quad);
}
});
return _view;
}
public void showImage (Mat img) {
ImageView imgView = (ImageView) getActivity().findViewById(R.id.sampleImageView);
//Mat mRgba = new Mat();
//mRgba = Utils.loadResource(MainAct.this, R.drawable.your_image,Highgui.CV_LOAD_IMAGE_COLOR);
Bitmap img2 = Bitmap.createBitmap(img.cols(), img.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(img, img2);
imgView.setImageBitmap(img2);
}
public File mediaStorageDir () {
File _mediaStorageDir = new File(Environment.getExternalStorageDirectory()
+ "/Android/data/"
+ getActivity().getApplicationContext().getPackageName());
return _mediaStorageDir;
}
public void storeImage(Mat matImg) {
Bitmap bitmapImg = Bitmap.createBitmap(matImg.cols(), matImg.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(matImg, bitmapImg);
String timeStamp = new SimpleDateFormat("ddMMyyyy_HHmm").format(new Date());
File mediaFile;
String mImageName="IMG_"+ timeStamp +".jpg";
mediaFile = new File(mediaStorageDir().getPath() + File.separator + mImageName);
File pictureFile = mediaFile;
try {
FileOutputStream fos = new FileOutputStream(pictureFile);
bitmapImg.compress(Bitmap.CompressFormat.PNG, 90, fos);
fos.close();
} catch (FileNotFoundException e) {
Log.d("FragmentMain", "File not found: " + e.getMessage());
} catch (IOException e) {
Log.d("FragmentMain", "Error accessing file: " + e.getMessage());
}
}

here is my trial code as a sample.
i hope it will be helpful. ( i will add some explanation about the code later)
Test Image ( edited your image. having an empty and invalid double mark )
(source: opencv.org)
Result Image
(source: opencv.org)
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
using namespace cv;
using namespace std;
int main( int argc, const char** argv )
{
Mat img = imread(argv[1]);
if(img.empty())
{
return -1;
}
Size dims(20,5); // this variable should be changed according input
Mat gray,thresh;
cvtColor(img, gray, COLOR_BGR2GRAY);
threshold(gray, thresh, 0, 255, THRESH_BINARY_INV + THRESH_OTSU);
Mat quad(img.size(), CV_8UC1); // should be improved
Mat results(img.size(), CV_8UC3);
vector<Point2f> quad_pts;
quad_pts.push_back(cv::Point2f(0, 0));
quad_pts.push_back(cv::Point2f(quad.cols, 0));
quad_pts.push_back(cv::Point2f(quad.cols, quad.rows));
quad_pts.push_back(cv::Point2f(0, quad.rows));
vector<Point2f> corners;
vector<vector<Point> > contours;
findContours(thresh.clone(), contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
for( size_t i = 0; i< contours.size(); i++ )
{
RotatedRect minRect = minAreaRect( Mat(contours[i]) );
// rotated rectangle
Point2f rect_points[4];
minRect.points( rect_points );
if(Rect(minRect.boundingRect()).width > img.cols / 2) // should be improved
for( int j = 0; j < 4; j++ )
{
Point2f pt = quad_pts[j];
Point2f nearest_pt = rect_points[0];
float dist = norm( pt - nearest_pt );
for( int k = 1; k < 4; k++ )
{
if( norm( pt - rect_points[k] ) < dist )
{
dist = norm( pt - rect_points[k] );
nearest_pt = rect_points[k];
}
}
corners.push_back( nearest_pt );
}
}
erode(thresh,thresh,Mat(),Point(-1,-1), 10); // should be improved
dilate(thresh,thresh,Mat(),Point(-1,-1), 5); // should be improved
Mat transmtx = getPerspectiveTransform(corners, quad_pts);
warpPerspective( img, results, transmtx, img.size()); // Create a Mat To Show results
warpPerspective( thresh, quad, transmtx, img.size());
resize(quad,quad,dims);
for(int i = 0; i < quad.cols; i++)
{
String answer = "";
answer += quad.at<uchar>(1,i) == 0 ? "" : "A";
answer += quad.at<uchar>(2,i) == 0 ? "" : "B";
answer += quad.at<uchar>(3,i) == 0 ? "" : "C";
answer += quad.at<uchar>(4,i) == 0 ? "" : "D";
if( answer.length() > 1 ) answer = "X"; // Double mark
int y = 0;
if( answer == "A" ) y = results.rows / dims.height;
if( answer == "B" ) y = results.rows / dims.height *2;
if( answer == "C" ) y = results.rows / dims.height *3;
if( answer == "D" ) y = results.rows / dims.height *4;
if( answer == "" ) answer = "[-]";
putText( results, answer, Point( 50* i + 15, 30 + y), FONT_HERSHEY_PLAIN, 2, Scalar(0,0,255),2);
}
imshow( "results", results );
waitKey(0);
return 0;
}
as a challenge to myself i tried to implement main part in JAVA ( a newcomer copy paste code )
Mat img = Imgcodecs.imread("test.jpg");
Mat gray = new Mat();
Mat thresh = new Mat();
//convert the image to black and white
Imgproc.cvtColor(img, gray, Imgproc.COLOR_BGR2GRAY);
//convert the image to black and white does (8 bit)
Imgproc.threshold(gray, thresh, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU);
Mat temp = thresh.clone();
//find the contours
Mat hierarchy = new Mat();
Mat corners = new Mat(4,1,CvType.CV_32FC2);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(temp, contours,hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
hierarchy.release();
for (int idx = 0; idx < contours.size(); idx++)
{
MatOfPoint contour = contours.get(idx);
MatOfPoint2f contour_points = new MatOfPoint2f(contour.toArray());
RotatedRect minRect = Imgproc.minAreaRect( contour_points );
Point[] rect_points = new Point[4];
minRect.points( rect_points );
if(minRect.size.height > img.width() / 2)
{
List<Point> srcPoints = new ArrayList<Point>(4);
srcPoints.add(rect_points[2]);
srcPoints.add(rect_points[3]);
srcPoints.add(rect_points[0]);
srcPoints.add(rect_points[1]);
corners = Converters.vector_Point_to_Mat(
srcPoints, CvType.CV_32F);
}
}
Imgproc.erode(thresh, thresh, new Mat(), new Point(-1,-1), 10);
Imgproc.dilate(thresh, thresh, new Mat(), new Point(-1,-1), 5);
Mat results = new Mat(1000,250,CvType.CV_8UC3);
Mat quad = new Mat(1000,250,CvType.CV_8UC1);
List<Point> dstPoints = new ArrayList<Point>(4);
dstPoints.add(new Point(0, 0));
dstPoints.add(new Point(1000, 0));
dstPoints.add(new Point(1000, 250));
dstPoints.add(new Point(0, 250));
Mat quad_pts = Converters.vector_Point_to_Mat(
dstPoints, CvType.CV_32F);
Mat transmtx = Imgproc.getPerspectiveTransform(corners, quad_pts);
Imgproc.warpPerspective( img, results, transmtx, new Size(1000,250));
Imgproc.warpPerspective( thresh, quad, transmtx, new Size(1000,250));
Imgproc.resize(quad,quad,new Size(20,5));
Imgcodecs.imwrite("results.png",quad);
here is the (20x5px) result image :

I imrove #sturkmen' s code.
fragment_main.xml
<FrameLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context="{your package name}.FragmentMain">
<!-- TODO: Update blank fragment layout -->
<LinearLayout
android:orientation="vertical"
android:layout_width="match_parent"
android:layout_height="match_parent">
<Button
android:id="#+id/btnTest"
android:layout_width="match_parent"
android:layout_height="80dp"
android:text="Test" />
<ImageView
android:id="#+id/sampleImageView"
android:layout_width="match_parent"
android:layout_height="150dp"
android:layout_centerHorizontal="true"/>
</LinearLayout>
</framelayout>
AndroidManifest.xml
Add this line for write permission.
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />
FragmentMain.java
IMAGE FILE: Add Internal Storage/Android/Data/Your Package Folder/test.JPG
public View onCreateView(LayoutInflater inflater, ViewGroup container,
Bundle savedInstanceState) {
View _view = inflater.inflate(R.layout.fragment_main, container, false);
Button btnTest = (Button) _view.findViewById(R.id.btnTest);
btnTest.setOnClickListener(new View.OnClickListener() {
#Override
public void onClick(View v) {
Mat img = Imgcodecs.imread(mediaStorageDir().getPath() + "/" + "test.JPG");
if (img.empty()) {
Log.d("FragmentMain", "Empty Image");
}
Size dims = new Size (20,5);
Mat gray = new Mat();
Mat thresh = new Mat();
//convert the image to black and white
Imgproc.cvtColor(img, gray, Imgproc.COLOR_BGR2GRAY);
storeImage(gray);
//convert the image to black and white does (8 bit)
Imgproc.threshold(gray, thresh, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU);
storeImage(thresh);
Mat temp = thresh.clone();
//find the contours
Mat hierarchy = new Mat();
Mat corners = new Mat(4,1, CvType.CV_32FC2);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(temp, contours,hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
hierarchy.release();
for (int idx = 0; idx < contours.size(); idx++)
{
MatOfPoint contour = contours.get(idx);
MatOfPoint2f contour_points = new MatOfPoint2f(contour.toArray());
RotatedRect minRect = Imgproc.minAreaRect( contour_points );
Point[] rect_points = new Point[4];
minRect.points( rect_points );
if(minRect.size.height > img.width() / 2)
{
List<Point> srcPoints = new ArrayList<Point>(4);
srcPoints.add(rect_points[2]);
srcPoints.add(rect_points[3]);
srcPoints.add(rect_points[0]);
srcPoints.add(rect_points[1]);
corners = Converters.vector_Point_to_Mat(
srcPoints, CvType.CV_32F);
}
}
Imgproc.erode(thresh, thresh, new Mat(), new Point(-1,-1), 10);
storeImage(thresh);
Imgproc.dilate(thresh, thresh, new Mat(), new Point(-1,-1), 5);
storeImage(thresh);
Mat results = new Mat(1000,250,CvType.CV_8UC3);
Mat quad = new Mat(1000,250,CvType.CV_8UC1);
List<Point> dstPoints = new ArrayList<Point>(4);
dstPoints.add(new Point(0, 0));
dstPoints.add(new Point(1000, 0));
dstPoints.add(new Point(1000, 250));
dstPoints.add(new Point(0, 250));
Mat quad_pts = Converters.vector_Point_to_Mat(
dstPoints, CvType.CV_32F);
Mat transmtx = Imgproc.getPerspectiveTransform(corners, quad_pts);
Imgproc.warpPerspective( img, results, transmtx, new Size(1000,250));
Imgproc.warpPerspective( thresh, quad, transmtx, new Size(1000,250));
Imgproc.resize(quad, quad, new Size(20,5));
Imgcodecs.imwrite("results.png",quad);
//store image
storeImage(quad);
//show image
showImage(quad);
System.out.println( quad.dump() );
for(int i = 0; i < quad.cols(); i++)
{
int size = (int) (quad.total() * quad.channels());
byte[] tmp = new byte[size];
String answer = "";
double[] d = new double[0];
d = quad.get(1, i);
answer += d[0] == 0 ? "" : "A";
d = quad.get(2, i);
answer += d[0] == 0 ? "" : "B";
d = quad.get(3, i);
answer += d[0] == 0 ? "" : "C";
d = quad.get(4, i);
answer += d[0] == 0 ? "" : "D";
if( answer.length() > 1 ) answer = "X"; // Double mark
int y = 0;
if( answer.equals("A")) y = results.rows() / (int) dims.height;
if( answer.equals("B")) y = results.rows() / (int) dims.height *2;
if( answer.equals("C")) y = results.rows() / (int) dims.height *3;
if( answer.equals("D")) y = results.rows() / (int) dims.height *4;
if( answer == "" ) answer = "[-]";
Imgproc.putText( results, answer, new Point( 50* i + 15, 30 + y), Core.FONT_HERSHEY_PLAIN, 2, new Scalar(0,0,255),2);
}
//store image
storeImage(results);
//show image
showImage(results);
}
});
public void showImage (Mat img) {
ImageView imgView = (ImageView) getActivity().findViewById(R.id.sampleImageView);
//Mat mRgba = new Mat();
//mRgba = Utils.loadResource(MainAct.this, R.drawable.your_image,Highgui.CV_LOAD_IMAGE_COLOR);
Bitmap img2 = Bitmap.createBitmap(img.cols(), img.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(img, img2);
imgView.setImageBitmap(img2);
}
public File mediaStorageDir () {
File _mediaStorageDir = new File(Environment.getExternalStorageDirectory()
+ "/Android/data/"
+ getActivity().getApplicationContext().getPackageName());
return _mediaStorageDir;
}
public void storeImage(Mat matImg) {
Bitmap bitmapImg = Bitmap.createBitmap(matImg.cols(), matImg.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(matImg, bitmapImg);
String timeStamp = new SimpleDateFormat("ddMMyyyy_HHmm").format(new Date());
File mediaFile;
String mImageName="IMG_"+ timeStamp +".jpg";
mediaFile = new File(mediaStorageDir().getPath() + File.separator + mImageName);
File pictureFile = mediaFile;
try {
FileOutputStream fos = new FileOutputStream(pictureFile);
bitmapImg.compress(Bitmap.CompressFormat.PNG, 90, fos);
fos.close();
} catch (FileNotFoundException e) {
Log.d("FragmentMain", "File not found: " + e.getMessage());
} catch (IOException e) {
Log.d("FragmentMain", "Error accessing file: " + e.getMessage());
}
}

OpenCV with Laplacian formula to detect image is blur or not in Android

In Ios we can:
Is there a way to detect if an image is blurry?
I don't know how to detect image is blur or not in Android or Java?

private void opencvProcess() {
BitmapFactory.Options options = new BitmapFactory.Options();
options.inDither = true;
options.inPreferredConfig = Bitmap.Config.ARGB_8888;
Bitmap image = decodeSampledBitmapFromFile(picFilePath, options, 2000, 2000);
int l = CvType.CV_8UC1; //8-bit grey scale image
Mat matImage = new Mat();
Utils.bitmapToMat(image, matImage);
Mat matImageGrey = new Mat();
Imgproc.cvtColor(matImage, matImageGrey, Imgproc.COLOR_BGR2GRAY);
Bitmap destImage;
destImage = Bitmap.createBitmap(image);
Mat dst2 = new Mat();
Utils.bitmapToMat(destImage, dst2);
Mat laplacianImage = new Mat();
dst2.convertTo(laplacianImage, l);
Imgproc.Laplacian(matImageGrey, laplacianImage, CvType.CV_8U);
Mat laplacianImage8bit = new Mat();
laplacianImage.convertTo(laplacianImage8bit, l);
Bitmap bmp = Bitmap.createBitmap(laplacianImage8bit.cols(), laplacianImage8bit.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(laplacianImage8bit, bmp);
int[] pixels = new int[bmp.getHeight() * bmp.getWidth()];
bmp.getPixels(pixels, 0, bmp.getWidth(), 0, 0, bmp.getWidth(), bmp.getHeight()); // bmp为轮廓图
int maxLap = -16777216; // 16m
for (int pixel : pixels) {
if (pixel > maxLap)
maxLap = pixel;
}
int soglia = -6118750;
if (maxLap <= soglia) {
System.out.println("is blur image");
}
soglia += 6118750;
maxLap += 6118750;
LogUtil.log("图片位置=" + picFilePath
+ "\nimage.w=" + image.getWidth() + ", image.h=" + image.getHeight()
+ "\nmaxLap= " + maxLap + "(清晰范围:0~6118750)"
+ "\n" + Html.fromHtml("<font color='#eb5151'><b>" + (maxLap <= soglia ? "模糊" : "清晰") + "</b></font>"));
opencvEnd = true;
isBlur = maxLap <= soglia;
}

Android Multithreading

I have a piece of code that is removing bitmap background, at first the code was taking about 40s> to remove each bitmap background but I optimized to about 12son a hauwei y320 -u30 with quadcore 1.3ghz each and 6s on Galaxy s3 Quadcore although this is pretty good compared to the first product it is not good enough I want it start ranging in about 2s to 3s for the huawei due to the fact that the base user will probably have a low end device, I am using an async task with fixed fixedthreadpool of 2 and thread priority of Process.setThreadPriority(Process.THREAD_PRIORITY_BACKGROUND +
Process.THREAD_PRIORITY_MORE_FAVORABLE) but I was wondering, I know multi threading is the ability of running multiple tasks per single time frame but isnt there a way I can run 2 or 3 threads on one task, for example in my case run the threads on my background removal code, am sure this can yield better performance due to the fact that at the time am running this code there is no other thread within my app that is also running, I have all resources per run time of my code, I looked up online but I cannot find anything related to that, below is the my code:
public class ImageBackgrndRemover extends AppCompatActivity {
private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {
#Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS:
{
Log.i(TAG, "OpenCV loaded successfully");
//instantia
if(!alreadyRun) {
BackgroundRemover remover = null;
if(remover == null)
{
remover = new BackgroundRemover();
remover.executeOnExecutor(AsyncTask.DUAL_THREAD_EXECUTOR);
}
}
} break;
default:
{
super.onManagerConnected(status);
} break;
}
}
};
private LoadingAnimation add;
ImageView iv;
Scalar color;
Mat dst;
private boolean alreadyRun;
public static final String TAG = "Grabcut demo";
#Override
public void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_image_backgrnd_remover);
iv = (ImageView) this.findViewById(R.id.imagePreview);
}
private int calculatePercentage(int percentage, int target)
{
int k = (int)(target*(percentage/100.0f));
return k;
}
private Bitmap backGrndErase()
{
color = new Scalar(255, 0, 0, 255);
dst = new Mat();
Bitmap bitmap = BitmapFactory.decodeResource(getResources(), R.drawable.myshirt);
Log.d(TAG, "bitmap: " + bitmap.getWidth() + "x" + bitmap.getHeight());
bitmap = ResizeImage.getResizedBitmap(bitmap, calculatePercentage(40, bitmap.getWidth()), calculatePercentage(40, bitmap.getHeight()));
// Bitmap bitmap2 = ImageCornerMoulder.getRoundedCornerBitmap(bmp, calculatePercentage(5, bmp.getHeight()));
bitmap = bitmap.copy(Bitmap.Config.ARGB_8888, true);
Log.d(TAG, "bitmap 8888: " + bitmap.getWidth() + "x" + bitmap.getHeight());
//GrabCut part
Mat img = new Mat();
Utils.bitmapToMat(bitmap, img);
Log.d(TAG, "img: " + img);
int r = img.rows();
int c = img.cols();
Point p1 = new Point(c/10, r/10);
Point p2 = new Point(c-c/10, r-r/10);
int border = 20;
int border2 = border + border;
Rect rect2 = new Rect(border,border,img.cols()-border2,img.rows()-border2);
Rect rect = new Rect(p1,p2);
Log.d(TAG, "rect: " + rect);
Mat mask = new Mat();
debugger(""+mask.type());
mask.setTo(new Scalar(125));
Mat fgdModel = new Mat();
fgdModel.setTo(new Scalar(255, 255, 255));
Mat bgdModel = new Mat();
bgdModel.setTo(new Scalar(255, 255, 255));
Mat imgC3 = new Mat();
Imgproc.cvtColor(img, imgC3, Imgproc.COLOR_RGBA2RGB);
Log.d(TAG, "imgC3: " + imgC3);
Log.d(TAG, "Grabcut begins");
Imgproc.grabCut(imgC3, mask, rect2, bgdModel, fgdModel, 2, Imgproc.GC_INIT_WITH_RECT);
Mat source = new Mat(1, 1, CvType.CV_8U, new Scalar(3.0));
Core.compare(mask, source, mask, Core.CMP_EQ);
Mat foreground = new Mat(img.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
img.copyTo(foreground, mask);
Imgproc.rectangle(img, p1, p2, color);
Mat background = new Mat();
try {
background = Utils.loadResource(getApplicationContext(),
R.drawable.blackcolor );
} catch (IOException e) {
e.printStackTrace();
}
Mat tmp = new Mat();
Imgproc.resize(background, tmp, img.size());
background = tmp;
Mat tempMask = new Mat(foreground.size(), CvType.CV_8UC1, new Scalar(255, 255, 255));
Imgproc.cvtColor(foreground, tempMask, 6/* COLOR_BGR2GRAY */);
//Imgproc.threshold(tempMask, tempMask, 254, 255, 1 /* THRESH_BINARY_INV */);
Mat vals = new Mat(1, 1, CvType.CV_8UC3, new Scalar(0.0));
dst = new Mat();
background.setTo(vals, tempMask);
Imgproc.resize(foreground, tmp, mask.size());
foreground = tmp;
Core.add(background, foreground, dst, tempMask);
Log.d(TAG, "Convert to Bitmap");
//removing blackbaground started
/***
Mat tmp2 = new Mat();
Mat alpha = new Mat();
Imgproc.cvtColor(dst, tmp2, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(tmp2, alpha, 100, 255, Imgproc.THRESH_BINARY);
List<Mat> rgb = new ArrayList<Mat>(3);
Core.split(dst, rgb);
List<Mat> rgba = new ArrayList<Mat>(4);
rgba.add(rgb.get(0));
rgba.add(rgb.get(1));
rgba.add(rgb.get(2));
rgba.add(alpha);
Core.merge(rgba, dst);
Bitmap output = Bitmap.createBitmap(dst.width(), dst.height(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(dst, output);
***/
//removing back ended
Utils.matToBitmap(dst, bitmap);
//release MAT part
img.release();
imgC3.release();
mask.release();
fgdModel.release();
bgdModel.release();
alreadyRun = true;
return bitmap;
}
private void showLoadingIndicator()
{
android.support.v4.app.FragmentManager fm = getSupportFragmentManager();
add = LoadingAnimation.newInstance("b");
add.show(fm, "");
add.setCancelable(false);
}
private void dismissLoadingIndicator()
{
try {
add.dismiss();
}catch (Exception e)
{
e.printStackTrace();
}
}
private class BackgroundRemover extends AsyncTask<Void, Void, Bitmap>
{
#Override
protected void onPreExecute()
{
showLoadingIndicator();
}
#Override
protected Bitmap doInBackground(Void... voids) {
Process.setThreadPriority(Process.THREAD_PRIORITY_BACKGROUND +
Process.THREAD_PRIORITY_MORE_FAVORABLE);
try{
return backGrndErase();
}catch (Exception e)
{
System.err.println("Failed to remove background");
}
return null;
}
#Override
protected void onPostExecute(Bitmap bitmap) {
// iv.setBackgroundResource(R.drawable.blackcolor);
iv.setImageBitmap(bitmap);
dismissLoadingIndicator();
}
}
#Override
public void onResume()
{
super.onResume();
if (!OpenCVLoader.initDebug()) {
Log.d(TAG, "Internal OpenCV library not found. Using OpenCV Manager for initialization");
OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_3_0_0, this, mLoaderCallback);
} else {
Log.d(TAG, "OpenCV library found inside package. Using it!");
mLoaderCallback.onManagerConnected(LoaderCallbackInterface.SUCCESS);
}
}
private static Bitmap makeBlackTransparent(Bitmap image) {
// convert image to matrix
Mat src = new Mat(image.getWidth(), image.getHeight(), CvType.CV_8UC4);
Utils.bitmapToMat(image, src);
// init new matrices
Mat dst = new Mat(image.getWidth(), image.getHeight(), CvType.CV_8UC4);
Mat tmp = new Mat(image.getWidth(), image.getHeight(), CvType.CV_8UC4);
Mat alpha = new Mat(image.getWidth(), image.getHeight(), CvType.CV_8UC4);
// convert image to grayscale
Imgproc.cvtColor(src, tmp, Imgproc.COLOR_BGR2GRAY);
// threshold the image to create alpha channel with complete transparency in black background region and zero transparency in foreground object region.
Imgproc.threshold(tmp, alpha, 100, 255, Imgproc.THRESH_BINARY);
// split the original image into three single channel.
List<Mat> rgb = new ArrayList<Mat>(3);
Core.split(src, rgb);
// Create the final result by merging three single channel and alpha(BGRA order)
List<Mat> rgba = new ArrayList<Mat>(4);
rgba.add(rgb.get(0));
rgba.add(rgb.get(1));
rgba.add(rgb.get(2));
rgba.add(alpha);
Core.merge(rgba, dst);
// convert matrix to output bitmap
Bitmap output = Bitmap.createBitmap(image.getWidth(), image.getHeight(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(dst, output);
return output;
}
public void debugger(String s){
Log.v("", "########### " + s);
}
}