java截图后怎么用tesseract 文字识别
网上传的代码示例大多是在Windows下安装Tesseract ORC后通过CMD命令操作进行图识别操作.而 Tess4j 针对Tesseract 提供了JNI支持,同时还提供了一些图片操作的工具类,提供比如图片放大,旋转,黑白处理,锐化 等用来提高识别率的操作.操作十分方便. T
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java 实现图片的文字识别
摘要图像识别是目前很热门的研究领域，涉及的知识很广，包括信息论、模式识别、模糊数学、图像编码、内容分类等等。本文仅对使用Java实现了一个简单的图像文本二值处理，关于识别并未实现。
步骤
建立文本字符模板二值矩阵
对测试字符进行二值矩阵化处理
代码
/*
* @(#)StdModelRepository.java
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Library General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*/
package cn.edu.ynu.sei.recognition.util;import java.awt.Image;import java.awt.image.BufferedImage;import java.io.File;import java.io.IOException;import java.util.ArrayList;import java.util.List;import java.util.logging.Level;import java.util.logging.Logger;import javax.imageio.ImageIO;/** * Hold character charImgs as standard model repository.
* @author 88250
* @version 1.0.0.0, Mar 20, 2008
*/
public class StdModelRepository {
/** * hold character images
*/ List charImgs = new ArrayList();
/** * default width of a character
*/ static int width = 16 /** * default height of a character
*/ static int height = 28 /** * standard character model matrix
*/ public int[][][] stdCharMatrix = new int[27][width][height];
/** * Default constructor.
*/ public StdModelRepository() {
BufferedImage lowercase = null try {
lowercase = ImageIO.read(new File("lowercase.png"));
} catch (IOException ex) {
Logger.getLogger(StdModelRepository.class.getName()).
log(Level.SEVERE, null, ex);
}
for (int i = 0 i 26 i++) {
charImgs.add(lowercase.getSubimage(i * width,
0,
width,
height));
}
for (int i = 0 i charImgs.size(); i++) {
Image image = charImgs.get(i);
int[] pixels = ImageUtils.getPixels(image,
image.getWidth(null),
image.getHeight(null));
stdCharMatrix[i] = ImageUtils.getSymbolMatrix(pixels, 0).clone();
ImageUtils.displayMatrix(stdCharMatrix[i]);
}
}
}
/*
* @(#)ImageUtils.java
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Library General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*/
package cn.edu.ynu.sei.recognition.util;import java.awt.Image;import java.awt.image.PixelGrabber;import java.util.logging.Level;import java.util.logging.Logger;/** * Mainipulation of image data.
* @author 88250
* @version 1.0.0.3, Mar 20, 2008
*/
public class ImageUtils {
/** * Return all of the pixel values of sepecified codeimage .* @param image the sepecified image
* @param width width of the image
* @param height height of the image
* @return */ public static int[] getPixels(Image image, int width, int height) {
int[] pixels = new int[width * height];
try {
new PixelGrabber(image, 0, 0, width, height, pixels, 0, width).grabPixels();
} catch (InterruptedException ex) {
Logger.getLogger(ImageUtils.class.getName()).
log(Level.SEVERE, null, ex);
}
return pixels;
}
资源来自：
怎么用java实现图片里面的数字识别
图片是由点组成（或者是别的方法），记录点的位置、颜色，控制点就行了。至于ocr，有难度，首先要制作文字的变化范围及整个字各部分的联系，这还是简单的。然后，图像分解就行了。额，我不会编程，稍微会点c++，所以这个回答就是假设如果我做这种程序的思路。
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文章标题：图片文字识别java代码 java识别图片中的二维码
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