Java OCR tesseract 图像智能字符识别技术 Java实现

/**
 * 
 * 
 * @author mjorcen
 * @email mjorcen@gmail.com
 * @dateTime Jun 19, 2014 3:42:16 PM
 * @version 1
 */
public class PB {
    static String path = "E:/test/code";

    public static void main(String[] args) {
        File file = new File(path);
        for (String string : file.list()) {
            File iFile = new File(path, string);
            if (iFile.isFile()) {
                pb2(string);
            }
        }
    }

    public static void pb2(String filename) {
        try {
            List<String> cmd = new LinkedList<String>();

            cmd.add("tesseract");
            cmd.add(filename);
            cmd.add(filename);
            ProcessBuilder pb = new ProcessBuilder(cmd);
            pb.redirectErrorStream(true);
            pb.directory(new File("E:/test/code"));
            Process p = pb.start();

            // 取得命令结果的输出流
            InputStream fis = p.getInputStream();
            // 用一个读输出流类去读
            InputStreamReader isr = new InputStreamReader(fis, "gbk");
            // 用缓冲器读行
            BufferedReader br = new BufferedReader(isr);
            String line = null;
            // 直到读完为止
            while ((line = br.readLine()) != null) {
                // System.out.println(line);
            }

            // 取得结果的输出流
            InputStream resultIs = new FileInputStream(new File(path, filename
                    + ".txt"));
            // 用一个读输出流类去读
            InputStreamReader resultIsr = new InputStreamReader(resultIs, "gbk");
            // 用缓冲器读行
            BufferedReader resultBr = new BufferedReader(resultIsr);
            line = null;
            // 直到读完为止
            while ((line = resultBr.readLine()) != null) {
                System.out.print(line);
            }
            System.out.print(",");
        } catch (Exception e) {
            System.out.print(e.toString());
        }
    }
}

uHx7,IXQO,\1ZYP,ZVBO,3237,5SYQ~,,87YF,\8KDN,CGPC,\c\IG\N,F\Z TA,J 9pc,Lpza,NBGC,N QW8,onwz,ox XJ,\P9FM,P PR鈥楿,QRG\I\,,RAZ v\,504i,VGPH,VPCI,\\I\M I,鈥楳J1,Y6H9\,Y OGP,

package cn.c.test3;

import java.awt.Color;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;

public class ClearImageHelper {

    public static void main(String[] args) throws IOException {

        File testDataDir = new File("E:\\test\\code");
        final String destDir = testDataDir.getAbsolutePath() + "/tmp";
        for (File file : testDataDir.listFiles()) {
            cleanImage(file, destDir);
        }

    }

    /**
     * 
     * @param sfile
     *            需要去噪的图像
     * @param destDir
     *            去噪后的图像保存地址
     * @throws IOException
     */
    public static void cleanImage(File sfile, String destDir)
            throws IOException {
        File destF = new File(destDir);
        if (!destF.exists()) {
            destF.mkdirs();
        }

        BufferedImage bufferedImage = ImageIO.read(sfile);
        int h = bufferedImage.getHeight();
        int w = bufferedImage.getWidth();

        // 灰度化
        int[][] gray = new int[w][h];
        for (int x = 0; x < w; x++) {
            for (int y = 0; y < h; y++) {
                int argb = bufferedImage.getRGB(x, y);
                // 图像加亮（调整亮度识别率非常高）
                int r = (int) (((argb >> 16) & 0xFF) * 1.1 + 30);
                int g = (int) (((argb >> 8) & 0xFF) * 1.1 + 30);
                int b = (int) (((argb >> 0) & 0xFF) * 1.1 + 30);
                if (r >= 255) {
                    r = 255;
                }
                if (g >= 255) {
                    g = 255;
                }
                if (b >= 255) {
                    b = 255;
                }
                gray[x][y] = (int) Math
                        .pow((Math.pow(r, 2.2) * 0.2973 + Math.pow(g, 2.2)
                                * 0.6274 + Math.pow(b, 2.2) * 0.0753), 1 / 2.2);
            }
        }

        // 二值化
        int threshold = ostu(gray, w, h);
        BufferedImage binaryBufferedImage = new BufferedImage(w, h,
                BufferedImage.TYPE_BYTE_BINARY);
        for (int x = 0; x < w; x++) {
            for (int y = 0; y < h; y++) {
                if (gray[x][y] > threshold) {
                    gray[x][y] |= 0x00FFFF;
                } else {
                    gray[x][y] &= 0xFF0000;
                }
                binaryBufferedImage.setRGB(x, y, gray[x][y]);
            }
        }

        // 矩阵打印
        for (int y = 0; y < h; y++) {
            for (int x = 0; x < w; x++) {
                if (isBlack(binaryBufferedImage.getRGB(x, y))) {
                    System.out.print("*");
                } else {
                    System.out.print(" ");
                }
            }
            System.out.println();
        }

        ImageIO.write(binaryBufferedImage, "jpg",
                new File(destDir, sfile.getName()));
    }

    public static boolean isBlack(int colorInt) {
        Color color = new Color(colorInt);
        if (color.getRed() + color.getGreen() + color.getBlue() <= 300) {
            return true;
        }
        return false;
    }

    public static boolean isWhite(int colorInt) {
        Color color = new Color(colorInt);
        if (color.getRed() + color.getGreen() + color.getBlue() > 300) {
            return true;
        }
        return false;
    }

    public static int isBlackOrWhite(int colorInt) {
        if (getColorBright(colorInt) < 30 || getColorBright(colorInt) > 730) {
            return 1;
        }
        return 0;
    }

    public static int getColorBright(int colorInt) {
        Color color = new Color(colorInt);
        return color.getRed() + color.getGreen() + color.getBlue();
    }

    public static int ostu(int[][] gray, int w, int h) {
        int[] histData = new int[w * h];
        // Calculate histogram
        for (int x = 0; x < w; x++) {
            for (int y = 0; y < h; y++) {
                int red = 0xFF & gray[x][y];
                histData[red]++;
            }
        }

        // Total number of pixels
        int total = w * h;

        float sum = 0;
        for (int t = 0; t < 256; t++)
            sum += t * histData[t];

        float sumB = 0;
        int wB = 0;
        int wF = 0;

        float varMax = 0;
        int threshold = 0;

        for (int t = 0; t < 256; t++) {
            wB += histData[t]; // Weight Background
            if (wB == 0)
                continue;

            wF = total - wB; // Weight Foreground
            if (wF == 0)
                break;

            sumB += (float) (t * histData[t]);

            float mB = sumB / wB; // Mean Background
            float mF = (sum - sumB) / wF; // Mean Foreground

            // Calculate Between Class Variance
            float varBetween = (float) wB * (float) wF * (mB - mF) * (mB - mF);

            // Check if new maximum found
            if (varBetween > varMax) {
                varMax = varBetween;
                threshold = t;
            }
        }

        return threshold;
    }
}