图形识别-基于opencv+java简单程序

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

2. import java.util.ArrayList;
3. import java.util.List;
5. import org.opencv.core.Core;
6. import org.opencv.core.CvType;
7. import org.opencv.core.Mat;
8. import org.opencv.core.Point;
9. import org.opencv.core.Scalar;
10. import org.opencv.core.Size;
11. import org.opencv.highgui.Highgui;
12. import org.opencv.imgproc.Imgproc;
14. /**
15. * @Description 背景去除 简单案列，只适合背景单一的图像
16. * @author XPY
17. * @date 2016年8月30日下午4:14:32
18. */
19. public class demo1 {
20. public static void main(String[] args) {
21. System.loadLibrary("opencv_java246");
22. Mat img = Highgui.imread("E:\opencv_img\source\1.jpg");//读图像
23. Mat new_img = doBackgroundRemoval(img);
24. Highgui.imwrite("E:\opencv_img\target\1.jpg",new_img);//写图像
25. }
27. private static Mat doBackgroundRemoval(Mat frame) {
28. // init
29. Mat hsvImg = new Mat();
30. List<Mat> hsvPlanes = new ArrayList<>();
31. Mat thresholdImg = new Mat();
33. int thresh_type = Imgproc.THRESH_BINARY_INV;
35. // threshold the image with the average hue value
36. hsvImg.create(frame.size(), CvType.CV_8U);
37. Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
38. Core.split(hsvImg, hsvPlanes);
40. // get the average hue value of the image
42. Scalar average = Core.mean(hsvPlanes.get(0));
43. double threshValue = average.val[0];
44. Imgproc.threshold(hsvPlanes.get(0), thresholdImg, threshValue, 179.0,
45. thresh_type);
47. Imgproc.blur(thresholdImg, thresholdImg, new Size(5, 5));
49. // dilate to fill gaps, erode to smooth edges
50. Imgproc.dilate(thresholdImg, thresholdImg, new Mat(),
51. new Point(-1, -1), 1);
52. Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1),
53. 3);
55. Imgproc.threshold(thresholdImg, thresholdImg, threshValue, 179.0,
56. Imgproc.THRESH_BINARY);
58. // create the new image
59. Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255,
60. 255, 255));
61. thresholdImg.convertTo(thresholdImg, CvType.CV_8U);
62. frame.copyTo(foreground, thresholdImg);// 掩膜图像复制
63. return foreground;
64. }
65. }

2.边缘检测

2. import org.opencv.core.Core;
3. import org.opencv.core.Mat;
4. import org.opencv.core.Size;
5. import org.opencv.highgui.Highgui;
6. import org.opencv.imgproc.Imgproc;
8. /**
9. * @Description 边缘检测
10. * @author XPY
11. * @date 2016年8月30日下午5:01:01
12. */
13. public class demo2 {
14. public static void main(String[] args) {
15. System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
16. Mat img = Highgui.imread("E:\face7.jpg");//读图像
17. Mat new_img = doCanny(img);
18. Highgui.imwrite("E:\opencv_img\target\2.jpg",new_img);//写图像
19. }
21. private static Mat doCanny(Mat frame)
22. {
23. // init
24. Mat grayImage = new Mat();
25. Mat detectedEdges = new Mat();
26. double threshold = 10;
27. // convert to grayscale
28. Imgproc.cvtColor(frame, grayImage, Imgproc.COLOR_BGR2GRAY);
29. // reduce noise with a 3x3 kernel
30. Imgproc.blur(grayImage, detectedEdges, new Size(3, 3));
31. // canny detector, with ratio of lower:upper threshold of 3:1
32. Imgproc.Canny(detectedEdges, detectedEdges, threshold, threshold * 3);
33. // using Canny's output as a mask, display the result
34. Mat dest = new Mat();
35. frame.copyTo(dest, detectedEdges);
36. return dest;
37. }
38. }

3.人脸检测技术 （靠边缘的和侧脸检测不准确）

2. import org.opencv.core.Core;
3. import org.opencv.core.Mat;
4. import org.opencv.core.MatOfRect;
5. import org.opencv.core.Point;
6. import org.opencv.core.Rect;
7. import org.opencv.core.Scalar;
8. import org.opencv.highgui.Highgui;
9. import org.opencv.objdetect.CascadeClassifier;
11. /**
12. *
13. * @Description 人脸检测技术 （靠边缘的和侧脸检测不准确）
14. * @author XPY
15. * @date 2016年9月1日下午4:47:33
16. */
17. public class demo3 {
19. public static void main(String[] args) {
20. System.out.println("Hello, OpenCV");
21. // Load the native library.
22. System.loadLibrary("opencv_java246");
23. new demo3().run();
24. }
27. public void run() {
28. System.out.println("Running DetectFaceDemo");
29. System.out.println(getClass().getResource("/haarcascade_frontalface_alt2.xml").getPath());
30. // Create a face detector from the cascade file in the resources
31. // directory.
32. //CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("haarcascade_frontalface_alt2.xml").getPath());
33. //Mat image = Highgui.imread(getClass().getResource("lena.png").getPath());
34. //注意：源程序的路径会多打印一个‘/’，因此总是出现如下错误
35. /*
36. * Detected 0 faces Writing faceDetection.png libpng warning: Image
37. * width is zero in IHDR libpng warning: Image height is zero in IHDR
38. * libpng error: Invalid IHDR data
39. */
40. //因此，我们将第一个字符去掉
41. String xmlfilePath=getClass().getResource("/haarcascade_frontalface_alt2.xml").getPath().substring(1);
42. CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);
43. Mat image = Highgui.imread("E:\face2.jpg");
44. // Detect faces in the image.
45. // MatOfRect is a special container class for Rect.
46. MatOfRect faceDetections = new MatOfRect();
47. faceDetector.detectMultiScale(image, faceDetections);
49. System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
51. // Draw a bounding box around each face.
52. for (Rect rect : faceDetections.toArray()) {
53. Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
54. }
56. // Save the visualized detection.
57. String filename = "E:\faceDetection.png";
58. System.out.println(String.format("Writing %s", filename));
59. System.out.println(filename);
60. Highgui.imwrite(filename, image);
61. }
63. }