Java OCR tesseract 图像智能字符识别技术 Java代码实现

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：

1. 
   
2. package com.zhy.test;
4. import java.io.BufferedReader;
6. import java.io.File;
7. import java.io.FileInputStream;
8. import java.io.InputStreamReader;
9. import java.util.ArrayList;
10. import java.util.List;
12. import org.jdesktop.swingx.util.OS;
14. public class OCRHelper
15. {
16. private final String LANG_OPTION = "-l";
17. private final String EOL = System.getProperty("line.separator");
18. /**
19. * 文件位置我防止在，项目同一路径
20. */
21. private String tessPath = new File("tesseract").getAbsolutePath();
23. /**
24. * @param imageFile
25. * 传入的图像文件
26. * @param imageFormat
27. * 传入的图像格式
28. * @return 识别后的字符串
29. */
30. public String recognizeText(File imageFile) throws Exception
31. {
32. /**
33. * 设置输出文件的保存的文件目录
34. */
35. File outputFile = new File(imageFile.getParentFile(), "output");
37. StringBuffer strB = new StringBuffer();
38. List<String> cmd = new ArrayList<String>();
39. if (OS.isWindowsXP())
40. {
41. cmd.add(tessPath + "\\tesseract");
42. } else if (OS.isLinux())
43. {
44. cmd.add("tesseract");
45. } else
46. {
47. cmd.add(tessPath + "\\tesseract");
48. }
49. cmd.add("");
50. cmd.add(outputFile.getName());
51. cmd.add(LANG_OPTION);
52. //cmd.add("chi_sim");
53. cmd.add("eng");
55. ProcessBuilder pb = new ProcessBuilder();
56. /**
57. *Sets this process builder's working directory.
58. */
59. pb.directory(imageFile.getParentFile());
60. cmd.set(1, imageFile.getName());
61. pb.command(cmd);
62. pb.redirectErrorStream(true);
63. Process process = pb.start();
64. // tesseract.exe 1.jpg 1 -l chi_sim
65. // Runtime.getRuntime().exec("tesseract.exe 1.jpg 1 -l chi_sim");
66. /**
67. * the exit value of the process. By convention, 0 indicates normal
68. * termination.
69. */
70. //System.out.println(cmd.toString());
71. int w = process.waitFor();
72. if (w == 0)// 0代表正常退出
73. {
74. BufferedReader in = new BufferedReader(new InputStreamReader(
75. new FileInputStream(outputFile.getAbsolutePath() + ".txt"),
76. "UTF-8"));
77. String str;
79. while ((str = in.readLine()) != null)
80. {
81. strB.append(str).append(EOL);
82. }
83. in.close();
84. } else
85. {
86. String msg;
87. switch (w)
88. {
89. case 1:
90. msg = "Errors accessing files. There may be spaces in your image's filename.";
91. break;
92. case 29:
93. msg = "Cannot recognize the image or its selected region.";
94. break;
95. case 31:
96. msg = "Unsupported image format.";
97. break;
98. default:
99. msg = "Errors occurred.";
100. }
101. throw new RuntimeException(msg);
102. }
103. new File(outputFile.getAbsolutePath() + ".txt").delete();
104. return strB.toString().replaceAll("\\s*", "");
105. }
106. }

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：

1. 
   
2. package com.zhy.test;
4. import java.io.File;
6. public class Test
7. {
8. public static void main(String[] args)
9. {
10. try
11. {
13. File testDataDir = new File("testdata");
14. System.out.println(testDataDir.listFiles().length);
15. int i = 0 ;
16. for(File file :testDataDir.listFiles())
17. {
18. i++ ;
19. String recognizeText = new OCRHelper().recognizeText(file);
20. System.out.print(recognizeText+"\t");
22. if( i % 5 == 0 )
23. {
24. System.out.println();
25. }
26. }
28. } catch (Exception e)
29. {
30. e.printStackTrace();
31. }
33. }
34. }

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。

----------------------------------------我的分割线-----------------------------------

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：

1. 
   
2. package com.zhy.test;
4. import java.awt.Color;
5. import java.awt.image.BufferedImage;
6. import java.io.File;
7. import java.io.IOException;
9. import javax.imageio.ImageIO;
11. public class ClearImageHelper
12. {
14. public static void main(String[] args) throws IOException
15. {
18. File testDataDir = new File("testdata");
19. final String destDir = testDataDir.getAbsolutePath()+"/tmp";
20. for (File file : testDataDir.listFiles())
21. {
22. cleanImage(file, destDir);
23. }
25. }
27. /**
28. *
29. * @param sfile
30. * 需要去噪的图像
31. * @param destDir
32. * 去噪后的图像保存地址
33. * @throws IOException
34. */
35. public static void cleanImage(File sfile, String destDir)
36. throws IOException
37. {
38. File destF = new File(destDir);
39. if (!destF.exists())
40. {
41. destF.mkdirs();
42. }
44. BufferedImage bufferedImage = ImageIO.read(sfile);
45. int h = bufferedImage.getHeight();
46. int w = bufferedImage.getWidth();
48. // 灰度化
49. int[][] gray = new int[w][h];
50. for (int x = 0; x < w; x++)
51. {
52. for (int y = 0; y < h; y++)
53. {
54. int argb = bufferedImage.getRGB(x, y);
55. // 图像加亮（调整亮度识别率非常高）
56. int r = (int) (((argb >> 16) & 0xFF) * 1.1 + 30);
57. int g = (int) (((argb >> 8) & 0xFF) * 1.1 + 30);
58. int b = (int) (((argb >> 0) & 0xFF) * 1.1 + 30);
59. if (r >= 255)
60. {
61. r = 255;
62. }
63. if (g >= 255)
64. {
65. g = 255;
66. }
67. if (b >= 255)
68. {
69. b = 255;
70. }
71. gray[x][y] = (int) Math
72. .pow((Math.pow(r, 2.2) * 0.2973 + Math.pow(g, 2.2)
73. * 0.6274 + Math.pow(b, 2.2) * 0.0753), 1 / 2.2);
74. }
75. }
77. // 二值化
78. int threshold = ostu(gray, w, h);
79. BufferedImage binaryBufferedImage = new BufferedImage(w, h,
80. BufferedImage.TYPE_BYTE_BINARY);
81. for (int x = 0; x < w; x++)
82. {
83. for (int y = 0; y < h; y++)
84. {
85. if (gray[x][y] > threshold)
86. {
87. gray[x][y] |= 0x00FFFF;
88. } else
89. {
90. gray[x][y] &= 0xFF0000;
91. }
92. binaryBufferedImage.setRGB(x, y, gray[x][y]);
93. }
94. }
96. // 矩阵打印
97. for (int y = 0; y < h; y++)
98. {
99. for (int x = 0; x < w; x++)
100. {
101. if (isBlack(binaryBufferedImage.getRGB(x, y)))
102. {
103. System.out.print("*");
104. } else
105. {
106. System.out.print(" ");
107. }
108. }
109. System.out.println();
110. }
112. ImageIO.write(binaryBufferedImage, "jpg", new File(destDir, sfile
113. .getName()));
114. }
116. public static boolean isBlack(int colorInt)
117. {
118. Color color = new Color(colorInt);
119. if (color.getRed() + color.getGreen() + color.getBlue() <= 300)
120. {
121. return true;
122. }
123. return false;
124. }
126. public static boolean isWhite(int colorInt)
127. {
128. Color color = new Color(colorInt);
129. if (color.getRed() + color.getGreen() + color.getBlue() > 300)
130. {
131. return true;
132. }
133. return false;
134. }
136. public static int isBlackOrWhite(int colorInt)
137. {
138. if (getColorBright(colorInt) < 30 || getColorBright(colorInt) > 730)
139. {
140. return 1;
141. }
142. return 0;
143. }
145. public static int getColorBright(int colorInt)
146. {
147. Color color = new Color(colorInt);
148. return color.getRed() + color.getGreen() + color.getBlue();
149. }
151. public static int ostu(int[][] gray, int w, int h)
152. {
153. int[] histData = new int[w * h];
154. // Calculate histogram
155. for (int x = 0; x < w; x++)
156. {
157. for (int y = 0; y < h; y++)
158. {
159. int red = 0xFF & gray[x][y];
160. histData[red]++;
161. }
162. }
164. // Total number of pixels
165. int total = w * h;
167. float sum = 0;
168. for (int t = 0; t < 256; t++)
169. sum += t * histData[t];
171. float sumB = 0;
172. int wB = 0;
173. int wF = 0;
175. float varMax = 0;
176. int threshold = 0;
178. for (int t = 0; t < 256; t++)
179. {
180. wB += histData[t]; // Weight Background
181. if (wB == 0)
182. continue;
184. wF = total - wB; // Weight Foreground
185. if (wF == 0)
186. break;
188. sumB += (float) (t * histData[t]);
190. float mB = sumB / wB; // Mean Background
191. float mF = (sum - sumB) / wF; // Mean Foreground
193. // Calculate Between Class Variance
194. float varBetween = (float) wB * (float) wF * (mB - mF) * (mB - mF);
196. // Check if new maximum found
197. if (varBetween > varMax)
198. {
199. varMax = varBetween;
200. threshold = t;
201. }
202. }
204. return threshold;
205. }
206. }

好了，就到这里。如果这篇文章对你有用，赞一个吧~