用Java写一个车牌识别带图片，摄像头视频识别的代码

要实现车牌识别，可以使用OpenCV和Tesseract OCR库。下面是一个基于Java和OpenCV的车牌识别代码，可以处理图片和摄像头视频。

import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;

public class LicensePlateRecognition {

    public static void main(String[] args) {
        // 加载OpenCV库
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        // 读取图片
        Mat image = Imgcodecs.imread("car.jpg");

        // 在图片中检测车牌
        String licensePlate = detectLicensePlate(image);

        // 输出车牌号码
        System.out.println("License Plate: " + licensePlate);
    }

    public static String detectLicensePlate(Mat image) {
        // 加载车牌识别分类器
        CascadeClassifier classifier = new CascadeClassifier("haarcascade_russian_plate_number.xml");

        // 转化为灰度图
        Mat gray = new Mat();
        Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

        // 进行直方图均衡化
        Imgproc.equalizeHist(gray, gray);

        // 检测车牌
        MatOfRect plates = new MatOfRect();
        classifier.detectMultiScale(gray, plates);

        // 如果没有检测到车牌，则返回空字符串
        if (plates.empty()) {
            return "";
        }

        // 获取最大的车牌框
        Rect maxPlate = null;
        for (Rect plate : plates.toArray()) {
            if (maxPlate == null || plate.width > maxPlate.width) {
                maxPlate = plate;
            }
        }

        // 从车牌框中提取车牌区域
        Mat plateImage = new Mat(image, maxPlate);

        // 将车牌区域转化为灰度图
        Imgproc.cvtColor(plateImage, gray, Imgproc.COLOR_BGR2GRAY);

        // 进行二值化
        Imgproc.threshold(gray, gray, 0, 255, Imgproc.THRESH_BINARY_INV | Imgproc.THRESH_OTSU);

        // 调整车牌图像大小
        Imgproc.resize(gray, gray, new Size(400, 200));

        // 对车牌进行OCR识别
        String licensePlate = recognizeLicensePlate(gray);

        return licensePlate;
    }

    public static String recognizeLicensePlate(Mat image) {
        // 加载Tesseract OCR库
        TessBaseAPI api = new TessBaseAPI();
        api.Init(".", "eng");
        api.SetImage(image);

        // 进行OCR识别
        String licensePlate = api.GetUTF8Text().trim();

        // 关闭Tesseract OCR库
        api.End();

        return licensePlate;
    }
}

车牌识别分类器可以从OpenCV的GitHub仓库中下载，地址为：https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_russian_plate_number.xml

要使用摄像头进行车牌识别，可以使用JavaCV库，下面是一个基于JavaCV的车牌识别代码：

import org.bytedeco.opencv.opencv_core.*;
import org.bytedeco.opencv.opencv_videoio.VideoCapture;
import org.bytedeco.opencv.global.opencv_imgproc;
import org.bytedeco.tesseract.TessBaseAPI;

public class LicensePlateRecognition {

    public static void main(String[] args) {
        // 加载OpenCV库
        Loader.load(org.bytedeco.opencv.global.opencv_core.class);

        // 加载Tesseract OCR库
        TessBaseAPI api = new TessBaseAPI();
        api.Init(".", "eng");

        // 打开摄像头
        VideoCapture camera = new VideoCapture(0);

        // 循环读取视频帧
        Mat frame = new Mat();
        while (camera.read(frame)) {
            // 在视频中检测车牌
            String licensePlate = detectLicensePlate(frame, api);

            // 在视频中显示车牌号码
            opencv_imgproc.putText(frame, licensePlate, new Point(50, 50), opencv_imgproc.FONT_HERSHEY_SIMPLEX, 1.0, new Scalar(0, 0, 255, 0));

            // 显示视频帧
            imshow("License Plate Recognition", frame);

            // 按下ESC键退出循环
            if (waitKey(1) == 27) {
                break;
            }
        }

        // 关闭Tesseract OCR库
        api.End();
    }

    public static String detectLicensePlate(Mat image, TessBaseAPI api) {
        // 加载车牌识别分类器
        CascadeClassifier classifier = new CascadeClassifier("haarcascade_russian_plate_number.xml");

        // 转化为灰度图
        Mat gray = new Mat();
        opencv_imgproc.cvtColor(image, gray, opencv_imgproc.COLOR_BGR2GRAY);

        // 进行直方图均衡化
        opencv_imgproc.equalizeHist(gray, gray);

        // 检测车牌
        RectVector plates = new RectVector();
        classifier.detectMultiScale(gray, plates);

        // 如果没有检测到车牌，则返回空字符串
        if (plates.empty()) {
            return "";
        }

        // 获取最大的车牌框
        Rect maxPlate = null;
        for (int i = 0; i < plates.size(); i++) {
            Rect plate = plates.get(i);
            if (maxPlate == null || plate.width() > maxPlate.width()) {
                maxPlate = plate;
            }
        }

        // 从车牌框中提取车牌区域
        Mat plateImage = new Mat(image, maxPlate);

        // 将车牌区域转化为灰度图
        opencv_imgproc.cvtColor(plateImage, gray, opencv_imgproc.COLOR_BGR2GRAY);

        // 进行二值化
        opencv_imgproc.threshold(gray, gray, 0, 255, opencv_imgproc.THRESH_BINARY_INV | opencv_imgproc.THRESH_OTSU);

        // 调整车牌图像大小
        opencv_imgproc.resize(gray, gray, new Size(400, 200));

        // 对车牌进行OCR识别
        api.SetImage(gray);
        String licensePlate = api.GetUTF8Text().trim();

        return licensePlate;
    }

    public static void imshow(String title, Mat image) {
        CanvasFrame frame = new CanvasFrame(title);
        frame.setDefaultCloseOperation(WindowConstants.EXIT_ON_CLOSE);
        frame.showImage(new OpenCVFrameConverter.ToMat().convert(image));
    }

    public static int waitKey(int delay) {
        return (int) CanvasFrame.waitKey(delay);
    }
}