opencv图形识别方案(图形识别-基于opencv)
opencv图形识别方案(图形识别-基于opencv)1.背景去除 简单案列,只适合背景单一的图像 2.边缘检测3.人脸检测技术 (靠边缘的和侧脸检测不准确)
opencv的全称是:Open Source Computer Vision Library。OpenCV是一个基于BSD许可(开源)发行的跨平台计算机视觉库,可以运行在Linux、Windows、Android和Mac OS操作系统上。它轻量级而且高效——由一系列 C 函数和少量 C 类构成,同时提供了Python、Ruby、MATLAB等语言的接口,实现了图像处理和计算机视觉方面的很多通用算法。
OpenCV用C 语言编写,它的主要接口也是C 语言,但是依然保留了大量的C语言接口。该库也有大量的Python java and MATLAB/OCTAVE (版本2.5)的接口。这些语言的API接口函数可以通过在线文档获得。如今也提供对于C# Ch Ruby的支持。
本文着重讲述opencv java的实现程序,关于opencv的如何引入dll库等操作以及c的实现就不在这里概述了
直接开始,首先下载opencv,引入opencv-246.jar包以及对应dll库
1.背景去除 简单案列,只适合背景单一的图像
- import java.util.ArrayList;
- import java.util.List;
- import org.opencv.core.Core;
- import org.opencv.core.CvType;
- import org.opencv.core.Mat;
- import org.opencv.core.Point;
- import org.opencv.core.Scalar;
- import org.opencv.core.Size;
- import org.opencv.highgui.Highgui;
- import org.opencv.imgproc.Imgproc;
- /**
- * @Description 背景去除 简单案列,只适合背景单一的图像
- * @author XPY
- * @date 2016年8月30日下午4:14:32
- */
- public class demo1 {
- public static void main(String[] args) {
- System.loadLibrary("opencv_java246");
- Mat img = Highgui.imread("E:\\opencv_img\\source\\1.jpg");//读图像
- Mat new_img = doBackgroundRemoval(img);
- Highgui.imwrite("E:\\opencv_img\\target\\1.jpg" new_img);//写图像
- }
- private static Mat doBackgroundRemoval(Mat frame) {
- // init
- 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(frame.size() CvType.CV_8U);
- Imgproc.cvtColor(frame hsvImg Imgproc.COLOR_BGR2HSV);
- Core.split(hsvImg hsvPlanes);
- // get the average hue value of the image
- Scalar average = Core.mean(hsvPlanes.get(0));
- double threshValue = average.val[0];
- Imgproc.threshold(hsvPlanes.get(0) thresholdImg threshValue 179.0
- thresh_type);
- Imgproc.blur(thresholdImg thresholdImg new Size(5 5));
- // 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)
- 3);
- Imgproc.threshold(thresholdImg thresholdImg threshValue 179.0
- Imgproc.THRESH_BINARY);
- // create the new image
- Mat foreground = new Mat(frame.size() CvType.CV_8UC3 new Scalar(255
- 255 255));
- thresholdImg.convertTo(thresholdImg CvType.CV_8U);
- frame.copyTo(foreground thresholdImg);// 掩膜图像复制
- return foreground;
- }
- }
2.边缘检测
- import org.opencv.core.Core;
- import org.opencv.core.Mat;
- import org.opencv.core.Size;
- import org.opencv.highgui.Highgui;
- import org.opencv.imgproc.Imgproc;
- /**
- * @Description 边缘检测
- * @author XPY
- * @date 2016年8月30日下午5:01:01
- */
- public class demo2 {
- public static void main(String[] args) {
- System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
- Mat img = Highgui.imread("E:\\face7.jpg");//读图像
- Mat new_img = doCanny(img);
- Highgui.imwrite("E:\\opencv_img\\target\\2.jpg" new_img);//写图像
- }
- private static Mat doCanny(Mat frame)
- {
- // init
- Mat grayImage = new Mat();
- Mat detectedEdges = new Mat();
- double threshold = 10;
- // convert to grayscale
- Imgproc.cvtColor(frame 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 threshold threshold * 3);
- // using Canny's output as a mask display the result
- Mat dest = new Mat();
- frame.copyTo(dest detectedEdges);
- return dest;
- }
- }
3.人脸检测技术 (靠边缘的和侧脸检测不准确)
- 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;
- /**
- *
- * @Description 人脸检测技术 (靠边缘的和侧脸检测不准确)
- * @author XPY
- * @date 2016年9月1日下午4:47:33
- */
- public class demo3 {
- public static void main(String[] args) {
- System.out.println("Hello OpenCV");
- // Load the native library.
- System.loadLibrary("opencv_java246");
- new demo3().run();
- }
- public void run() {
- System.out.println("\nRunning DetectFaceDemo");
- System.out.println(getClass().getResource("/haarcascade_frontalface_alt2.xml").getPath());
- // Create a face detector from the cascade file in the resources
- // directory.
- //CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("haarcascade_frontalface_alt2.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("/haarcascade_frontalface_alt2.xml").getPath().substring(1);
- CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);
- Mat image = Highgui.imread("E:\\face2.jpg");
- // 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 = "E:\\faceDetection.png";
- System.out.println(String.format("Writing %s" filename));
- System.out.println(filename);
- Highgui.imwrite(filename image);
- }
- }