Java OCR tesseract 图像智能文字字符识别技术实例代码

2019-11-26 11:59:35

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接着上一篇OCR所说的，上一篇给大家介绍了tesseract 在命令行的简单用法，当然了要继承到我们的程序中，还是需要代码实现的，下面给大家分享下Java实现的例子。

拿代码扫描上面的图片，然后输出结果。主要思想就是利用Java调用系统任务。

下面是核心代码：

package com.zhy.test;  import java.io.BufferedReader;  import java.io.File; import java.io.FileInputStream; import java.io.InputStreamReader; import java.util.ArrayList; import java.util.List;  import org.jdesktop.swingx.util.OS;  public class OCRHelper {  private final String LANG_OPTION = "-l";  private final String EOL = System.getProperty("line.separator");  /**   * 文件位置我防止在，项目同一路径   */  private String tessPath = new File("tesseract").getAbsolutePath();   /**   * @param imageFile   *   传入的图像文件   * @param imageFormat   *   传入的图像格式   * @return 识别后的字符串   */  public String recognizeText(File imageFile) throws Exception  {   /**    * 设置输出文件的保存的文件目录    */   File outputFile = new File(imageFile.getParentFile(), "output");    StringBuffer strB = new StringBuffer();   List<String> cmd = new ArrayList<String>();   if (OS.isWindowsXP())   {    cmd.add(tessPath + "//tesseract");   } else if (OS.isLinux())   {    cmd.add("tesseract");   } else   {    cmd.add(tessPath + "//tesseract");   }   cmd.add("");   cmd.add(outputFile.getName());   cmd.add(LANG_OPTION); //  cmd.add("chi_sim");   cmd.add("eng");    ProcessBuilder pb = new ProcessBuilder();   /**    *Sets this process builder's working directory.    */   pb.directory(imageFile.getParentFile());   cmd.set(1, imageFile.getName());   pb.command(cmd);   pb.redirectErrorStream(true);   Process process = pb.start();   // tesseract.exe 1.jpg 1 -l chi_sim   // Runtime.getRuntime().exec("tesseract.exe 1.jpg 1 -l chi_sim");   /**    * the exit value of the process. By convention, 0 indicates normal    * termination.    */ //  System.out.println(cmd.toString());   int w = process.waitFor();   if (w == 0)// 0代表正常退出   {    BufferedReader in = new BufferedReader(new InputStreamReader(      new FileInputStream(outputFile.getAbsolutePath() + ".txt"),      "UTF-8"));    String str;     while ((str = in.readLine()) != null)    {     strB.append(str).append(EOL);    }    in.close();   } else   {    String msg;    switch (w)    {    case 1:     msg = "Errors accessing files. There may be spaces in your image's filename.";     break;    case 29:     msg = "Cannot recognize the image or its selected region.";     break;    case 31:     msg = "Unsupported image format.";     break;    default:     msg = "Errors occurred.";    }    throw new RuntimeException(msg);   }   new File(outputFile.getAbsolutePath() + ".txt").delete();   return strB.toString().replaceAll("//s*", "");  } }

代码很简单，中间那部分ProcessBuilder其实就类似Runtime.getRuntime().exec("tesseract.exe 1.jpg 1 -l chi_sim")，大家不习惯的可以使用Runtime。

测试代码：

package com.zhy.test;  import java.io.File;  public class Test {  public static void main(String[] args)  {   try   {        File testDataDir = new File("testdata");    System.out.println(testDataDir.listFiles().length);    int i = 0 ;    for(File file :testDataDir.listFiles())    {     i++ ;     String recognizeText = new OCRHelper().recognizeText(file);     System.out.print(recognizeText+"/t");      if( i % 5 == 0 )     {      System.out.println();     }    }       } catch (Exception e)   {    e.printStackTrace();   }   } }

输出结果：

对比第一张图片，是不是很完美~哈哈，当然了如果你只需要实现验证码的读写，那么上面就足够了。下面继续普及图像处理的知识。

当然了，有时候图片被扭曲或者模糊的很厉害，很不容易识别，所以下面我给大家介绍一个去噪的辅助类，绝对碉堡了，先看下效果图。

来张特写：

一个类，不依赖任何jar，把图像中的干扰线消灭了，是不是很给力，然后再拿这样的图片去识别，会不会效果更好呢，嘿嘿，大家自己实验~

代码：

package com.zhy.test;  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("testdata");   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;  } }

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