JAVA识别图形验证码

用HttpClient模拟客户端浏览器注册发帖。但是碰到了图形验证码的问题了，对单数字的验证码，通过一些OCR引擎，如：tesseract，AspriseOCR很容易解决问题。但碰到如CSDN论坛这中图形验证码就比较麻烦，必须先通过预处理。使图象二值化，黑白灰度，增加亮度。     package myfilter;  import java.io.*;  import java.awt.image.*;  import java.awt.geom.AffineTransform;  import java.awt.color.ColorSpace;  import java.awt.image.ConvolveOp;  import java.awt.image.Kernel;  import java.awt.image.BufferedImage;  import javax.imageio.ImageIO;  import java.awt.Toolkit;  import java.awt.Image;  public class MyImgFilter {  BufferedImage image;  private int iw, ih;  private int[] pixels;  public MyImgFilter(BufferedImage image) {  this.image = image;  iw = image.getWidth();  ih = image.getHeight();  pixels = new int[iw * ih];  }  public BufferedImage changeGrey() {  PixelGrabber pg = new PixelGrabber(image.getSource(), 0, 0, iw, ih, pixels,0, iw);  try {  pg.grabPixels();  } catch (InterruptedException e) {  e.printStackTrace();  }  // 设定二值化的域值，默认值为100  int grey = 100;  // 对图像进行二值化处理，Alpha值保持不变  ColorModel cm = ColorModel.getRGBdefault();  for (int i = 0; i < iw * ih; i++) {  int red, green, blue;  int alpha = cm.getAlpha(pixels[i]);  if (cm.getRed(pixels[i]) > grey) {  red = 255;  } else {  red = 0;  }  if (cm.getGreen(pixels[i]) > grey) {  green = 255;  } else {  green = 0;  }  if (cm.getBlue(pixels[i]) > grey) {  blue = 255;  } else {  blue = 0;  }  pixels[i] = alpha << 24 | red << 16 | green << 8 | blue; //通过移位重新构成某一点像素的RGB值  }  // 将数组中的象素产生一个图像  Image tempImg=Toolkit.getDefaultToolkit().createImage(new MemoryImageSource(iw,ih, pixels, 0, iw));  image = new BufferedImage(tempImg.getWidth(null),tempImg.getHeight(null), BufferedImage.TYPE_INT_BGR );  image.createGraphics().drawImage(tempImg, 0, 0, null);  return image;  }  public BufferedImage getMedian() {  PixelGrabber pg = new PixelGrabber(image.getSource(), 0, 0, iw, ih,  pixels,  0, iw);  try {  pg.grabPixels();  } catch (InterruptedException e) {  e.printStackTrace();  }  // 对图像进行中值滤波，Alpha值保持不变  ColorModel cm = ColorModel.getRGBdefault();  for (int i = 1; i < ih - 1; i++) {  for (int j = 1; j < iw - 1; j++) {  int red, green, blue;  int alpha = cm.getAlpha(pixels[i * iw + j]);  // int red2 = cm.getRed(pixels[(i - 1) * iw + j]);  int red4 = cm.getRed(pixels[i * iw + j - 1]);  int red5 = cm.getRed(pixels[i * iw + j]);  int red6 = cm.getRed(pixels[i * iw + j + 1]);  // int red8 = cm.getRed(pixels[(i + 1) * iw + j]);  // 水平方向进行中值滤波  if (red4 >= red5) {  if (red5 >= red6) {  red = red5;  } else {  if (red4 >= red6) {  red = red6;  } else {  red = red4;  }  }  } else {  if (red4 > red6) {  red = red4;  } else {  if (red5 > red6) {  red = red6;  } else {  red = red5;  }  }  }  int green4 = cm.getGreen(pixels[i * iw + j - 1]);  int green5 = cm.getGreen(pixels[i * iw + j]);  int green6 = cm.getGreen(pixels[i * iw + j + 1]);  // 水平方向进行中值滤波  if (green4 >= green5) {  if (green5 >= green6) {  green = green5;  } else {  if (green4 >= green6) {  green = green6;  } else {  green = green4;  }  }  } else {  if (green4 > green6) {  green = green4;  } else {  if (green5 > green6) {  green = green6;  } else {  green = green5;  }  }  }  // int blue2 = cm.getBlue(pixels[(i - 1) * iw + j]);  int blue4 = cm.getBlue(pixels[i * iw + j - 1]);  int blue5 = cm.getBlue(pixels[i * iw + j]);  int blue6 = cm.getBlue(pixels[i * iw + j + 1]);  // int blue8 = cm.getBlue(pixels[(i + 1) * iw + j]);  // 水平方向进行中值滤波  if (blue4 >= blue5) {  if (blue5 >= blue6) {  blue = blue5;  } else {  if (blue4 >= blue6) {  blue = blue6;  } else {  blue = blue4;  }  }  } else {  if (blue4 > blue6) {  blue = blue4;  } else {  if (blue5 > blue6) {  blue = blue6;  } else {  blue = blue5;  }  }  }  pixels[i * iw +  j] = alpha << 24 | red << 16 | green << 8 | blue;  }  }  // 将数组中的象素产生一个图像  Image tempImg=Toolkit.getDefaultToolkit().createImage(new MemoryImageSource(iw,ih, pixels, 0, iw));  image = new BufferedImage(tempImg.getWidth(null),tempImg.getHeight(null), BufferedImage.TYPE_INT_BGR );  image.createGraphics().drawImage(tempImg, 0, 0, null);  return image;  }  public BufferedImage getGrey() {  ColorConvertOp ccp=new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_GRAY), null);  return image=ccp.filter(image,null);  }  //Brighten using a linear formula that increases all color values  public BufferedImage getBrighten() {  RescaleOp rop=new RescaleOp(1.25f, 0, null);  return image=rop.filter(image,null);  }  //Blur by "convolving" the image with a matrix  public BufferedImage getBlur() {  float[] data = {  .1111f, .1111f, .1111f,  .1111f, .1111f, .1111f,  .1111f, .1111f, .1111f, };  ConvolveOp cop = new ConvolveOp(new Kernel(3, 3, data));  return image=cop.filter(image,null);  }  // Sharpen by using a different matrix  public BufferedImage getSharpen() {  float[] data = {  0.0f, -0.75f, 0.0f,  -0.75f, 4.0f, -0.75f,  0.0f, -0.75f, 0.0f};  ConvolveOp cop = new ConvolveOp(new Kernel(3, 3, data));  return image=cop.filter(image,null);  }  // 11) Rotate the image 180 degrees about its center point  public BufferedImage getRotate() {  AffineTransformOp atop=new AffineTransformOp(AffineTransform.getRotateInstance(Math.PI,image.getWidth()/2,image.getHeight()/2),  AffineTransformOp.TYPE_NEAREST_NEIGHBOR);  return image=atop.filter(image,null);  }  public BufferedImage getProcessedImg()  {  return image;  }  public static void main(String[] args) throws IOException {  FileInputStream fin=new FileInputStream(args[0]);  BufferedImage bi=ImageIO.read(fin);  MyImgFilter flt=new MyImgFilter(bi);  flt.changeGrey();  flt.getGrey();  flt.getBrighten();  bi=flt.getProcessedImg();  String pname=args[0].substring(0,args[0].lastIndexOf("."));  File file = new File(pname+".jpg");  ImageIO.write(bi, "jpg", file);  }  }  运行java myfilter.MyImgFilter t6.bmp，请确认图片t6.bmp与myfilter目录在同一目录下。  顺便说一下，在JDK1.5下，ImageIO可以输出JPG，BMP，PNG三种格式图片，但不支持GIF图片输出。