java 利用orc智能识别图像字符技术，虽然说不能够百分百识别，但还算有点用。package com.ocr;
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;
/**
*
* 图像过滤,增强OCR识别成功率
*
*/
public class ImageFilter {
private BufferedImage image;
private int iw, ih;
private int[] pixels;
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 = 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 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();
fo
2021-09-30 16:52:00
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