请你帮我用JAVA编写一个能识别数学公式的OCR代码

数学公式识别是一个比较复杂的任务，需要结合多个算法和库来完成。以下是一个基本的Java代码框架，可以作为参考：

import java.awt.image.BufferedImage;
import java.io.File;
import java.util.ArrayList;
import java.util.List;

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfByte;
import org.opencv.core.Rect;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

import ij.ImagePlus;
import ij.process.ImageProcessor;
import net.sourceforge.tess4j.ITesseract;
import net.sourceforge.tess4j.Tesseract;
import net.sourceforge.tess4j.TesseractException;

public class MathOCR {
    
    // 图像二值化阈值
    private static final int THRESHOLD = 120;
    
    // 字符宽度和高度的最小值和最大值
    private static final int MIN_WIDTH = 5;
    private static final int MAX_WIDTH = 300;
    private static final int MIN_HEIGHT = 5;
    private static final int MAX_HEIGHT = 300;
    
    // 字符识别器
    private static ITesseract tesseract = new Tesseract();
    
    static {
        // 设置Tesseract的语言
        tesseract.setLanguage("eng");
    }
    
    public static void main(String[] args) {
        // 加载OpenCV库
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
        
        // 读取输入图像
        String imagePath = "input.png";
        Mat image = Imgcodecs.imread(imagePath);
        
        // 预处理图像
        Mat gray = new Mat();
        Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);
        Imgproc.threshold(gray, gray, THRESHOLD, 255, Imgproc.THRESH_BINARY_INV);
        Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3));
        Imgproc.erode(gray, gray, kernel);
        Imgproc.dilate(gray, gray, kernel);
        
        // 字符分割
        List<Rect> charRects = new ArrayList<>();
        Mat hierarchy = new Mat();
        List<MatOfPoint> contours = new ArrayList<>();
        Imgproc.findContours(gray, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
        for (int i = 0; i < contours.size(); i++) {
            Rect rect = Imgproc.boundingRect(contours.get(i));
            if (rect.width > MIN_WIDTH && rect.width < MAX_WIDTH && rect.height > MIN_HEIGHT && rect.height < MAX_HEIGHT) {
                charRects.add(rect);
            }
        }
        
        // 对每个字符进行识别
        StringBuilder sb = new StringBuilder();
        for (Rect charRect : charRects) {
            Mat charImage = gray.submat(charRect);
            BufferedImage bufferedImage = MatToBufferedImage(charImage);
            String result = recognizeCharacter(bufferedImage);
            sb.append(result);
        }
        
        // 输出识别结果
        System.out.println(sb.toString());
    }
    
    // 将OpenCV的Mat对象转换为Java的BufferedImage对象
    private static BufferedImage MatToBufferedImage(Mat matrix) {
        MatOfByte mob = new MatOfByte();
        Imgcodecs.imencode(".png", matrix, mob);
        byte[] byteArray = mob.toArray();
        BufferedImage image = null;
        try {
            image = javax.imageio.ImageIO.read(new java.io.ByteArrayInputStream(byteArray));
        } catch (Exception e) {
            e.printStackTrace();
        }
        return image;
    }
    
    // 对单个字符进行识别
    private static String recognizeCharacter(BufferedImage image) {
        String result = "";
        try {
            result = tesseract.doOCR(image);
        } catch (TesseractException e) {
            e.printStackTrace();
        }
        return result.trim();
    }
}

这个代码框架包含了图像预处理、字符分割和字符识别等步骤，但是仅作为示例，可能需要根据具体的场景进行调整和优化。另外，需要注意的是，这个代码框架依赖于OpenCV和Tesseract两个库，需要在项目中添加这两个库的引用。