例子使用的版本为3.4.0，安装配置网上资料比较多。
代码为本地测试时候的版本，所以会有点乱。
import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.utils.Converters;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
/**
* @author liuxf
* @date 2018/10/22 14:28
* @param
* @return
*/
public class OpenCVJavaTest2 {
static{ System.loadLibrary(Core.NATIVE_LIBRARY_NAME); }
public static void main(String[] args) {
String imgUrl = "F:\\1.jpg";
Mat src = Imgcodecs.imread(imgUrl ,1);
Mat src_gray = new Mat();
test1(src,src_gray);
}
public static void test1(Mat src ,Mat src_gray){
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
List<MatOfPoint> markContours = new ArrayList<MatOfPoint>();
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
/**图片太小就放大**/
if (src.width()*src.height()<90000){
Imgproc.resize(src,src,new Size(800,600));
}
Mat src_all=src.clone();
//彩色图转灰度图
Imgproc.cvtColor(src ,src_gray ,Imgproc.COLOR_RGB2GRAY);
//对图像进行平滑处理
Imgproc.GaussianBlur(src_gray, src_gray, new Size(3,3), 0);
/**Imgcodecs.imwrite("F:\\output\\EH.jpg", src_gray);**/
Imgproc.Canny(src_gray,src_gray,112,255);
/**Imgcodecs.imwrite("F:\\output\\1-2.jpg", src_gray);**/
Mat hierarchy = new Mat();
Imgproc.findContours(src_gray ,contours ,hierarchy ,Imgproc.RETR_TREE ,Imgproc.CHAIN_APPROX_NONE);
for ( int i = 0; i< contours.size(); i++ ) {
MatOfPoint2f newMtx = new MatOfPoint2f( contours.get(i).toArray() );
RotatedRect rotRect = Imgproc.minAreaRect( newMtx );
double w = rotRect.size.width;
double h = rotRect.size.height;
double rate = Math.max(w, h)/Math.min(w, h) ;
/***
* 长短轴比小于1.3，总面积大于60
*/
if (rate < 1.3 && w < src_gray.cols()/4 && h<src_gray.rows()/4 && Imgproc.contourArea(contours.get(i))>60) {
/***
* 计算层数，二维码角框有五层轮廓（有说六层），这里不计自己这一层，有4个以上子轮廓则标记这一点
*/
double[] ds = hierarchy.get(0, i);
if (ds != null && ds.length>3){
int count =0;
if (ds[3] == -1){/**最外层轮廓排除*/
continue;
}
/***
* 计算所有子轮廓数量
*/
while ((int) ds[2] !=-1){
++count;
ds = hierarchy.get(0 ,(int) ds[2]);
}
if (count >= 4){
markContours.add(contours.get(i));
}
}
}
}
/**
* 这部分代码画框，调试用**/
for(int i=0; i<markContours.size(); i++){
Imgproc.drawContours(src_all,markContours,i,new Scalar(0,255,0) ,-1);
}
Imgcodecs.imwrite("F:\\output\\2-1.jpg", src_all);
/***
* 二维码有三个角轮廓，少于三个的无法定位放弃，多余三个的循环裁剪出来
*/
if (markContours.size() < 3){
return;
}else{
for (int i=0; i<markContours.size()-2; i++){
List<MatOfPoint> threePointList = new ArrayList<>();
for (int j=i+1;j<markContours.size()-1; j++){
for (int k=j+1;k<markContours.size();k++){
threePointList.add(markContours.get(i));
threePointList.add(markContours.get(j));
threePointList.add(markContours.get(k));
capture(threePointList ,src ,i+"-"+j+"-"+k);
threePointList.clear();
}
}
}
}
}
/***
* 另一种实现，识别能力比第一种弱
* @param src
* @param src_gray
*/
public static void test2(Mat src,Mat src_gray){
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
List<MatOfPoint> markContours = new ArrayList<MatOfPoint>();
if (src.width()*src.height()<90000){
Imgproc.resize(src,src,new Size(800,600));
}
Mat src_all=src.clone();
Mat threshold_output = new Mat();
//彩色图转灰度图
Imgproc.cvtColor(src ,src_gray ,Imgproc.COLOR_RGB2GRAY);
//对图像进行平滑处理
Imgproc.blur(src_gray ,src_gray ,new Size(3,3));
Imgproc.equalizeHist(src_gray,src_gray);
//指定112阀值进行二值化
Imgproc.threshold(src_gray ,threshold_output,112,255 ,Imgproc.THRESH_BINARY );
/**Imgcodecs.imwrite("F:\\output\\1-2.jpg", threshold_output);**/
Mat hierarchy = new Mat();
Imgproc.findContours(threshold_output ,contours ,hierarchy ,Imgproc.RETR_TREE ,Imgproc.CHAIN_APPROX_SIMPLE);
int c=0,ic=0,area=0;
int parentIdx=-1;
for ( int i = 0; i< contours.size(); i++ ) {
double[] ds = hierarchy.get(0, i);
int k=i;
if (ds == null) {
continue;
}
if (ds != null && ds.length>3){
int count =0;
if (ds[3] == -1){
continue;
}
while ((int) ds[2] !=-1){
++count;
ds = hierarchy.get(0 ,(int) ds[2]);
}
if (count >= 2){
markContours.add(contours.get(i));
}
}
}
Point[] point = new Point[markContours.size()];
for(int i=0; i<markContours.size(); i++)
{
point[i] = centerCal(markContours.get(i));
}
}
/**
* 对图片进行矫正，裁剪
* @param contours
* @param src
* @param idx
*/
public static void capture(List<MatOfPoint> contours ,Mat src ,String idx){
Point[] pointthree = new Point[3];
for(int i=0; i<contours.size(); i++)
{
pointthree[i] = centerCal(contours.get(i));
}
/**画线
* **/
Mat sline = src.clone();
Imgproc.line(sline ,pointthree[0],pointthree[1] ,new Scalar(0,0,255),2);
Imgproc.line(sline ,pointthree[1],pointthree[2] ,new Scalar(0,0,255),2);
Imgproc.line(sline ,pointthree[0],pointthree[2] ,new Scalar(0,0,255),2);
Imgcodecs.imwrite("F:\\output\\cvRio-"+idx+".jpg", sline);
double[] ca = new double[2];
double[] cb = new double[2];
ca[0] = pointthree[1].x - pointthree[0].x;
ca[1] = pointthree[1].y - pointthree[0].y;
cb[0] = pointthree[2].x - pointthree[0].x;
cb[1] = pointthree[2].y - pointthree[0].y;
/* if (Math.max(ca[0],cb[0])/Math.min(ca[0],cb[0]) > 1.5 || Math.max(ca[1],cb[1])/Math.min(ca[1],cb[1])>1.3){
return;
}*/
double angle1 = 180/3.1415*Math.acos((ca[0]*cb[0]+ca[1]*cb[1])/(Math.sqrt(ca[0]*ca[0]+ca[1]*ca[1])*Math.sqrt(cb[0]*cb[0]+cb[1]*cb[1])));
double ccw1;
if(ca[0]*cb[1] - ca[1]*cb[0] > 0) {
ccw1 = 0;
} else {
ccw1 = 1;
}
ca[0] = pointthree[0].x - pointthree[1].x;
ca[1] = pointthree[0].y - pointthree[1].y;
cb[0] = pointthree[2].x - pointthree[1].x;
cb[1] = pointthree[2].y - pointthree[1].y;
double angle2 = 180/3.1415*Math.acos((ca[0]*cb[0]+ca[1]*cb[1])/(Math.sqrt(ca[0]*ca[0]+ca[1]*ca[1])*Math.sqrt(cb[0]*cb[0]+cb[1]*cb[1])));
double ccw2;
if(ca[0]*cb[1] - ca[1]*cb[0] > 0) {
ccw2 = 0;
}else {
ccw2 = 1;
}
ca[0] = pointthree[1].x - pointthree[2].x;
ca[1] = pointthree[1].y - pointthree[2].y;
cb[0] = pointthree[0].x - pointthree[2].x;
cb[1] = pointthree[0].y - pointthree[2].y;
double angle3 = 180/3.1415*Math.acos((ca[0]*cb[0]+ca[1]*cb[1])/(Math.sqrt(ca[0]*ca[0]+ca[1]*ca[1])*Math.sqrt(cb[0]*cb[0]+cb[1]*cb[1])));
int ccw3;
if(ca[0]*cb[1] - ca[1]*cb[0] > 0) {
ccw3 = 0;
}else {
ccw3 = 1;
}
System.out.println("angle1:"+angle1+",angle2:"+angle2+",angle3:"+angle3);
if (Double.isNaN(angle1) || Double.isNaN(angle2) || Double.isNaN(angle3)){
return;
}
Point[] poly= new Point[4];
if(angle3>angle2 && angle3>angle1)
{
if(ccw3==1)
{
poly[1] = pointthree[1];
poly[3] = pointthree[0];
}
else
{
poly[1] = pointthree[0];
poly[3] = pointthree[1];
}
poly[0] = pointthree[2];
Point temp = new Point(pointthree[0].x + pointthree[1].x - pointthree[2].x , pointthree[0].y + pointthree[1].y - pointthree[2].y );
poly[2] = temp;
} else if(angle2>angle1 && angle2>angle3)
{
if(ccw2==1)
{
poly[1] = pointthree[0];
poly[3] = pointthree[2];
}
else
{
poly[1] = pointthree[2];
poly[3] = pointthree[0];
}
poly[0] = pointthree[1];
Point temp = new Point(pointthree[0].x + pointthree[2].x - pointthree[1].x , pointthree[0].y + pointthree[2].y - pointthree[1].y );
poly[2] = temp;
} else if(angle1>angle2 && angle1 > angle3)
{
if(ccw1==1)
{
poly[1] = pointthree[1];
poly[3] = pointthree[2];
}
else
{
poly[1] = pointthree[2];
poly[3] = pointthree[1];
}
poly[0] = pointthree[0];
Point temp = new Point(pointthree[1].x + pointthree[2].x - pointthree[0].x , pointthree[1].y + pointthree[2].y - pointthree[0].y );
poly[2] = temp;
}
Point[] trans=new Point[4];
int temp =50;
trans[0] = new Point(0+temp,0+temp);
trans[1] = new Point(0+temp,100+temp);
trans[2] = new Point(100+temp,100+temp);
trans[3] = new Point(100+temp,0+temp);
double maxAngle = Math.max(angle3,Math.max(angle1,angle2));
System.out.println(maxAngle);
if (maxAngle<75 || maxAngle>115){ /**二维码为直角，最大角过大或者过小都判断为不是二维码*/
return;
}
Mat perspectiveMmat=Imgproc.getPerspectiveTransform(Converters.vector_Point_to_Mat(Arrays.asList(poly),CvType.CV_32F),Converters.vector_Point_to_Mat(Arrays.asList(trans),CvType.CV_32F)); //warp_mat
Mat dst = new Mat();
//计算变换结果
Imgproc.warpPerspective(src,dst ,perspectiveMmat,src.size(),Imgproc.INTER_LINEAR);
Rect roiArea = new Rect(0, 0, 200, 200);
Mat dstRoi = new Mat(dst, roiArea);
Imgcodecs.imwrite("F:\\output\\dstRoi-"+idx+".jpg", dstRoi);
}
public static BufferedImage toBufferedImage(Mat m) {
int type = BufferedImage.TYPE_BYTE_GRAY;
if (m.channels() > 1) {
type = BufferedImage.TYPE_3BYTE_BGR;
}
int bufferSize = m.channels() * m.cols() * m.rows();
byte[] b = new byte[bufferSize];
m.get(0, 0, b); // get all the pixels
BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
System.arraycopy(b, 0, targetPixels, 0, b.length);
return image;
}
public static Point centerCal(MatOfPoint matOfPoint){
double centerx=0,centery=0;
int size = matOfPoint.cols();
MatOfPoint2f mat2f = new MatOfPoint2f( matOfPoint.toArray() );
RotatedRect rect = Imgproc.minAreaRect( mat2f );
Point vertices[] = new Point[4];
rect.points(vertices);
centerx = ((vertices[0].x + vertices[1].x)/2 + (vertices[2].x + vertices[3].x)/2)/2;
centery = ((vertices[0].y + vertices[1].y)/2 + (vertices[2].y + vertices[3].y)/2)/2;
Point point= new Point(centerx,centery);
return point;
}
}
需要说明一下：
double[] ds = hierarchy.get(0, i);
网上的资料ds[0]是后一个轮廓，ds[1]是前一个轮廓，ds[2]是父轮廓，ds[3]是内嵌轮廓， 但是通过实际测试ds[2]是内嵌轮廓 ds[3]是父轮廓 ，不知道跟版本有没有关系，还请自测。
2.网上大部分例子都是只定位3点的，但是实际图片如果模糊或者有干扰的话定位出来会是多个点，所以这里进行了循环的裁剪。
3.通过长短轴、面积和角度丢弃的点是没经过数值测试的
参考资料：
https://blog.csdn.net/iamqianrenzhan/article/details/79117119
