
当你完成图像分割之后,图像轮廓检测往往可以进一步筛选你要的目标,OpenCV中可以使用cv2.findContours来得到轮廓。
补充 :
再不少场景中,找轮廓的最小外接矩形是基本需求,opencv中minAreaRect得到的是一个带有旋转角度信息的rect,可以使用cv2.boxPoints(rect)来将其转为矩形的四个顶点坐标(浮点类型).你也可以使用cv2.polylines来绘制这样的轮廓信息
注意findContours参数的变化,在opencv4中,返回值只有contours和hierarchy ,这一点与opencv3中不同。对与轮廓的层级结构,比较难用,虽然可以通过轮廓的层级结构来进行索引你需要的轮廓,不过对于大部分机器视觉应用场景,二值化的结果有时候很难预料,单单通过这种层级关系索引,非常容易出错。所以,只找最外部结构的 cv2.RETR_EXTERNAL 是不是真香呢?
处理cv2.approxPolyDP()外,你也可以使用cv2.convexHull来求轮廓的近似凸包,其中凸形状内部--任意两点连线都在该形状内部。
clockwise :默认为False,即轮廓为逆时针方向进行排列;
returnPoints :设置为False会返回与凸包上对应的轮廓的点索引值,设置为True,则会返回凸包上的点坐标集,默认为True
对于opencv-python的提取图像轮廓部分有问题欢迎留言, Have Fun With OpenCV-Python, 下期见。
主要步骤1.读取一幅图片,并且对其进行二值化。2.对其进行形态学处理,减少孔洞等次要特征,保留其主要特征。3.进行边缘提取。4.进行形状轮廓匹配,得到其匹配值,从而判断是否是同一个形状。下面是演示代码:
#include
#include"opencv2/opencv.hpp"
usingnamespacestd
usingnamespacecv
intmain()
{
Matk=imread("E:/TestGit/8.jpg",0)
Matf
Matk1=imread("E:/TestGit/9.jpg",0)
Matf1
threshold(k,f,50,255,THRESH_BINARY)//对图像进行二值化
threshold(k1,f1,50,255,THRESH_BINARY)
Matcloserect=getStructuringElement(MORPH_RECT,Size(3,3))//进行结构算子生成
morphologyEx(f,f,MORPH_OPEN,closerect)
morphologyEx(f1,f1,MORPH_OPEN,closerect)//进行形态学开运算
Matdst=Mat::zeros(k.rows,k.cols,CV_8UC3)
Matdst1=Mat::zeros(k1.rows,k1.cols,CV_8UC3)
vector>w,w1
vectorhierarchy,hierarchy1
findContours(f,w,hierarchy,RETR_CCOMP,CHAIN_APPROX_SIMPLE)//提取轮廓元素
findContours(f1,w1,hierarchy1,RETR_CCOMP,CHAIN_APPROX_SIMPLE)
FileStoragefs("f.dat",FileStorage::WRITE)
fs
intidx=0
doubleffff=matchShapes(w[0],w1[0],CV_CONTOURS_MATCH_I3,1.0)//进行轮廓匹配
std::cout
system("pause")
return0
}
这样,我们就得到了轮廓边缘的提取和匹配,满足了需要。而不同的算子具有不同的匹配算子方法。
整个项目的结构图:编写DetectFaceDemo.java,代码如下:
[java] view
plaincopyprint?
package com.njupt.zhb.test
import org.opencv.core.Core
import org.opencv.core.Mat
import org.opencv.core.MatOfRect
import org.opencv.core.Point
import org.opencv.core.Rect
import org.opencv.core.Scalar
import org.opencv.highgui.Highgui
import org.opencv.objdetect.CascadeClassifier
//
// Detects faces in an image, draws boxes around them, and writes the results
// to "faceDetection.png".
//
public class DetectFaceDemo {
public void run() {
System.out.println("\nRunning DetectFaceDemo")
System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath())
// Create a face detector from the cascade file in the resources
// directory.
//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath())
//Mat image = Highgui.imread(getClass().getResource("lena.png").getPath())
//注意:源程序的路径会多打印一个‘/’,因此总是出现如下错误
/*
* Detected 0 faces Writing faceDetection.png libpng warning: Image
* width is zero in IHDR libpng warning: Image height is zero in IHDR
* libpng error: Invalid IHDR data
*/
//因此,我们将第一个字符去掉
String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1)
CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath)
Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1))
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect()
faceDetector.detectMultiScale(image, faceDetections)
System.out.println(String.format("Detected %s faces", faceDetections.toArray().length))
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0))
}
// Save the visualized detection.
String filename = "faceDetection.png"
System.out.println(String.format("Writing %s", filename))
Highgui.imwrite(filename, image)
}
}
package com.njupt.zhb.test
import org.opencv.core.Core
import org.opencv.core.Mat
import org.opencv.core.MatOfRect
import org.opencv.core.Point
import org.opencv.core.Rect
import org.opencv.core.Scalar
import org.opencv.highgui.Highgui
import org.opencv.objdetect.CascadeClassifier
//
// Detects faces in an image, draws boxes around them, and writes the results
// to "faceDetection.png".
//
public class DetectFaceDemo {
public void run() {
System.out.println("\nRunning DetectFaceDemo")
System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath())
// Create a face detector from the cascade file in the resources
// directory.
//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath())
//Mat image = Highgui.imread(getClass().getResource("lena.png").getPath())
//注意:源程序的路径会多打印一个‘/’,因此总是出现如下错误
/*
* Detected 0 faces Writing faceDetection.png libpng warning: Image
* width is zero in IHDR libpng warning: Image height is zero in IHDR
* libpng error: Invalid IHDR data
*/
//因此,我们将第一个字符去掉
String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1)
CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath)
Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1))
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect()
faceDetector.detectMultiScale(image, faceDetections)
System.out.println(String.format("Detected %s faces", faceDetections.toArray().length))
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0))
}
// Save the visualized detection.
String filename = "faceDetection.png"
System.out.println(String.format("Writing %s", filename))
Highgui.imwrite(filename, image)
}
}
3.编写测试类:
[java] view
plaincopyprint?
package com.njupt.zhb.test
public class TestMain {
public static void main(String[] args) {
System.out.println("Hello, OpenCV")
// Load the native library.
System.loadLibrary("opencv_java246")
new DetectFaceDemo().run()
}
}
//运行结果:
//Hello, OpenCV
//
//Running DetectFaceDemo
///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml
//Detected 8 faces
//Writing faceDetection.png
package com.njupt.zhb.test
public class TestMain {
public static void main(String[] args) {
System.out.println("Hello, OpenCV")
// Load the native library.
System.loadLibrary("opencv_java246")
new DetectFaceDemo().run()
}
}
//运行结果:
//Hello, OpenCV
//
//Running DetectFaceDemo
///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml
//Detected 8 faces
//Writing faceDetection.png
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