http://www.oschina.net/code/snippet_616487_15391 原网址:
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package com.coolinsoft.miaosha.util.ocr;
import java.awt.Color;
import java.awt.Graphics2D;
import java.awt.color.ColorSpace;
import java.awt.geom.AffineTransform;
import java.awt.image.AffineTransformOp;
import java.awt.image.BufferedImage;
import java.awt.image.ColorConvertOp;
import java.awt.image.ColorModel;
import java.awt.image.MemoryImageSource;
import java.awt.image.PixelGrabber;
import java.util.HashMap;
import java.util.Map;
public class ImageFilter {
private BufferedImage image;
private int iw, ih; //图片宽度、高度
private int [] pixels; //像素
public ImageFilter(BufferedImage image) {
this .image = image;
iw = image.getWidth();
ih = image.getHeight();
pixels = new int [iw * ih];
}
/** 图像二值化 */
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 = 150 ;
// 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;
}
// 将数组中的象素产生一个图像
return ImageIOHelper.imageProducerToBufferedImage( new MemoryImageSource(iw, ih,pixels, 0 , iw));
}
/** 提升清晰度,进行锐化 */
public BufferedImage sharp() {
PixelGrabber pg = new PixelGrabber(image.getSource(), 0 , 0 , iw, ih,
pixels, 0 , iw);
try {
pg.grabPixels();
} catch (InterruptedException e) {
e.printStackTrace();
}
// 象素的中间变量
int tempPixels[] = new int [iw * ih];
for ( int i = 0 ; i < iw * ih; i++) {
tempPixels[i] = pixels[i];
}
// 对图像进行尖锐化处理,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 alpha = cm.getAlpha(pixels[i * iw + j]);
// 对图像进行尖锐化
int red6 = cm.getRed(pixels[i * iw + j + 1 ]);
int red5 = cm.getRed(pixels[i * iw + j]);
int red8 = cm.getRed(pixels[(i + 1 ) * iw + j]);
int sharpRed = Math.abs(red6 - red5) + Math.abs(red8 - red5);
int green5 = cm.getGreen(pixels[i * iw + j]);
int green6 = cm.getGreen(pixels[i * iw + j + 1 ]);
int green8 = cm.getGreen(pixels[(i + 1 ) * iw + j]);
int sharpGreen = Math.abs(green6 - green5)
+ Math.abs(green8 - green5);
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]);
int sharpBlue = Math.abs(blue6 - blue5)
+ Math.abs(blue8 - blue5);
if (sharpRed > 255 ) {
sharpRed = 255 ;
}
if (sharpGreen > 255 ) {
sharpGreen = 255 ;
}
if (sharpBlue > 255 ) {
sharpBlue = 255 ;
}
tempPixels[i * iw + j] = alpha << 24 | sharpRed << 16
| sharpGreen << 8 | sharpBlue;
}
}
// 将数组中的象素产生一个图像
return ImageIOHelper
.imageProducerToBufferedImage( new MemoryImageSource(iw, ih,
tempPixels, 0 , iw));
}
public static int isWhite( int colorInt) {
Color color = new Color(colorInt);
if (color.getRed() + color.getGreen() + color.getBlue() > 600 ) {
return 1 ;
}
return 0 ;
}
public BufferedImage removeBackgroud(){
BufferedImage img = this .image;
img = img.getSubimage( 1 , 1 , img.getWidth() - 2 , img.getHeight() - 2 );
int width = img.getWidth();
int height = img.getHeight();
double subWidth = ( double ) width / 5.0 ;
for ( int i = 0 ; i < 5 ; i++) {
Map<Integer, Integer> map = new HashMap<Integer, Integer>();
for ( int x = ( int ) ( 1 + i * subWidth); x < (i + 1 ) * subWidth && x < width - 1 ; ++x) {
for ( int y = 0 ; y < height; ++y) {
if (isWhite(img.getRGB(x, y)) == 1 )
continue ;
if (map.containsKey(img.getRGB(x, y))) {
map.put(img.getRGB(x, y), map.get(img.getRGB(x, y)) + 1 );
} else {
map.put(img.getRGB(x, y), 1 );
}
}
}
int max = 0 ;
int colorMax = 0 ;
for (Integer color : map.keySet()) {
if (max < map.get(color)) {
max = map.get(color);
colorMax = color;
}
}
for ( int x = ( int ) ( 1 + i * subWidth); x < (i + 1 ) * subWidth && x < width - 1 ; ++x) {
for ( int y = 0 ; y < height; ++y) {
if (img.getRGB(x, y) != colorMax) {
img.setRGB(x, y, Color.WHITE.getRGB());
} else {
img.setRGB(x, y, Color.BLACK.getRGB());
}
}
}
}
return img;
}
/** 中值滤波 */
public BufferedImage median() {
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 green2 = cm.getGreen(pixels[(i - 1) * iw + j]);
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 ]);
// int green8 = cm.getGreen(pixels[(i + 1) * iw + j]);
// 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
return ImageIOHelper
.imageProducerToBufferedImage( new MemoryImageSource(iw, ih,
pixels, 0 , iw));
}
/** 线性灰度变换 */
public BufferedImage lineGrey() {
PixelGrabber pg = new PixelGrabber(image.getSource(), 0 , 0 , iw, ih,
pixels, 0 , iw);
try {
pg.grabPixels();
} catch (InterruptedException e) {
e.printStackTrace();
}
// 对图像进行进行线性拉伸,Alpha值保持不变
ColorModel cm = ColorModel.getRGBdefault();
for ( int i = 0 ; i < iw * ih; i++) {
int alpha = cm.getAlpha(pixels[i]);
int red = cm.getRed(pixels[i]);
int green = cm.getGreen(pixels[i]);
int blue = cm.getBlue(pixels[i]);
// 增加了图像的亮度
red = ( int ) ( 1.1 * red + 30 );
green = ( int ) ( 1.1 * green + 30 );
blue = ( int ) ( 1.1 * blue + 30 );
if (red >= 255 ) {
red = 255 ;
}
if (green >= 255 ) {
green = 255 ;
}
if (blue >= 255 ) {
blue = 255 ;
}
pixels[i] = alpha << 24 | red << 16 | green << 8 | blue;
}
// 将数组中的象素产生一个图像
return ImageIOHelper
.imageProducerToBufferedImage( new MemoryImageSource(iw, ih,
pixels, 0 , iw));
}
/** 转换为黑白灰度图 */
public BufferedImage grayFilter() {
ColorSpace cs = ColorSpace.getInstance(ColorSpace.CS_GRAY);
ColorConvertOp op = new ColorConvertOp(cs, null );
return op.filter(image, null );
}
/** 平滑缩放 */
public BufferedImage scaling( double s) {
AffineTransform tx = new AffineTransform();
tx.scale(s, s);
AffineTransformOp op = new AffineTransformOp(tx,
AffineTransformOp.TYPE_BILINEAR);
return op.filter(image, null );
}
public BufferedImage scale(Float s) {
int srcW = image.getWidth();
int srcH = image.getHeight();
int newW = Math.round(srcW * s);
int newH = Math.round(srcH * s);
// 先做水平方向上的伸缩变换
BufferedImage tmp = new BufferedImage(newW, newH, image.getType());
Graphics2D g = tmp.createGraphics();
for ( int x = 0 ; x < newW; x++) {
g.setClip(x, 0 , 1 , srcH);
// 按比例放缩
g.drawImage(image, x - x * srcW / newW, 0 , null );
}
// 再做垂直方向上的伸缩变换
BufferedImage dst = new BufferedImage(newW, newH, image.getType());
g = dst.createGraphics();
for ( int y = 0 ; y < newH; y++) {
g.setClip( 0 , y, newW, 1 );
// 按比例放缩
g.drawImage(tmp, 0 , y - y * srcH / newH, null );
}
return dst;
}
}
代码]将验证码抽取下来之后 零食存在本地 惊进行解析 跳至 [1] [全屏预览]
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转载于:https://www.cnblogs.com/leo3689/p/4419580.html
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