矩形二维码生成,解析(彩色、多个)

本文介绍了一种使用Java生成和解析二维码的方法,包括普通、带logo及彩色二维码的生成,以及彩色和多个二维码的解析。利用Google ZXing库,详细阐述了二维码生成参数设置、logo插入、图片灰度化与二值化等关键步骤。

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矩形二维码生成,解析(彩色、多个)

说明

  1. java生成普通二维码、带logo二维码、彩色二维码
  2. java解析彩色、多个二维码(一个图片上的多个二维码)
使用到的第三方jar包如下:
com.google.zxing:core:3.4.0
com.google.zxing:javase:3.4.0
生成二维码
package com.utils;

import com.google.zxing.*;
import com.google.zxing.client.j2se.BufferedImageLuminanceSource;
import com.google.zxing.common.BitMatrix;
import com.google.zxing.common.HybridBinarizer;
import com.google.zxing.multi.qrcode.QRCodeMultiReader;
import com.google.zxing.qrcode.decoder.ErrorCorrectionLevel;
import lombok.extern.slf4j.Slf4j;
import org.springframework.util.StringUtils;

import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.geom.AffineTransform;
import java.awt.geom.RoundRectangle2D;
import java.awt.image.AffineTransformOp;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;

@Slf4j
public class QRUtil {

    private static final String CHARSET = "UTF-8";
    private static final String FORMAT = "PNG";
    // 二维码尺寸
    private static final int QRCODE_SIZE = 150;
    // logo宽高
    private static final int LOGO_SIZE = 50;
    private static final HashMap<EncodeHintType, Object> ENCODE_HINTS = new HashMap<>();
    private static final HashMap<DecodeHintType, Object> DECODE_HINTS = new HashMap<>();

    static {
        ENCODE_HINTS.put(EncodeHintType.CHARACTER_SET, CHARSET);
        ENCODE_HINTS.put(EncodeHintType.ERROR_CORRECTION, ErrorCorrectionLevel.M);
        ENCODE_HINTS.put(EncodeHintType.MARGIN, 1);
        DECODE_HINTS.put(DecodeHintType.CHARACTER_SET, CHARSET);
    }


    /**
     * 生成二维码
     *
     * @param content  内容
     * @param destPath 存储地址
     */
    public static void encode(String content, String destPath) {
        encode(content, null, destPath);
    }

    /**
     * 生成二维码(包含logo)
     *
     * @param content  内容
     * @param logoPath logo地址
     * @param destPath 存储地址
     */
    public static void encode(String content, String logoPath, String destPath) {
        try {
            BufferedImage img = bufferedImage(content, logoPath);
            if (img != null) {
                ImageIO.write(img, FORMAT, new File(destPath));
            }
        } catch (IOException ignored) {
        }
    }

    /**
     * 生成二维码(包含logo)
     *
     * @param content  内容
     * @param logoPath logo地址
     */
    public static BufferedImage encodeBuffer(String content, String logoPath) {
        return bufferedImage(content, logoPath);
    }

    private static BufferedImage bufferedImage(String content, String logoPath) {
        BitMatrix bitMatrix = null;
        try {
            bitMatrix = new MultiFormatWriter().encode(content, BarcodeFormat.QR_CODE, QRCODE_SIZE, QRCODE_SIZE, ENCODE_HINTS);
        } catch (WriterException ignored) {
        }
        if (bitMatrix == null) {
            return null;
        }
        int width = bitMatrix.getWidth();
        int height = bitMatrix.getHeight();
        BufferedImage image = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
        for (int x = 0; x < width; x++) {
            for (int y = 0; y < height; y++) {
                // 此处可分别定制二维码和背景颜色
                image.setRGB(x, y, bitMatrix.get(x, y) ? Color.BLACK.getRGB() : Color.WHITE.getRGB());
            }
        }
        if (!StringUtils.isEmpty(logoPath)) {
            // 插入logo
            insertLogo(image, logoPath);
        }
        return image;
    }

    private static void insertLogo(BufferedImage source, String logoPath) {
        File file = new File(logoPath);
        if (!file.exists()) {
            return;
        }
        try {
            BufferedImage srcImage = ImageIO.read(file);
            int width = srcImage.getWidth(null);
            int height = srcImage.getHeight(null);
            Image destImage = srcImage.getScaledInstance(LOGO_SIZE, LOGO_SIZE, Image.SCALE_SMOOTH);
            // 按比例缩放logo图片
            if ((height > LOGO_SIZE) || (width > LOGO_SIZE)) {
                double ratio;
                if (height > width) {
                    ratio = Integer.valueOf(LOGO_SIZE).doubleValue() / height;
                } else {
                    ratio = Integer.valueOf(LOGO_SIZE).doubleValue() / width;
                }
                AffineTransformOp op = new AffineTransformOp(AffineTransform.getScaleInstance(ratio, ratio), null);
                destImage = op.filter(srcImage, null);
            }
            width = destImage.getWidth(null);
            height = destImage.getHeight(null);
            BufferedImage tag = new BufferedImage(width - 5, height - 5, BufferedImage.TYPE_INT_RGB);
            Graphics g = tag.getGraphics();
            g.drawImage(destImage, 0, 0, null);
            g.dispose();
            destImage = tag;

            Graphics2D graph = source.createGraphics();
            int x = (QRCODE_SIZE - width) / 2;
            int y = (QRCODE_SIZE - height) / 2;
            graph.drawImage(destImage, x, y, width, height, null);
            Shape shape = new RoundRectangle2D.Float(x, y, width, width, 5, 5);
            graph.setStroke(new BasicStroke(1f));
            graph.draw(shape);
            graph.dispose();
        } catch (IOException e) {
            log.error("read img error", e);
        }
    }

}
解析二维码
zxing自带的二值化(HybridBinarizer与GlobalHistogramBinarizer)并不能解决问题
因此要手动实现一下,解析二维码的主要流程:
1.将图片灰度化,使用加权灰度法(效果与opencv基本一致),尝试一次解析,失败则继续
2.对图片二值化(与opencv有差异,毕竟算法比不过它,暂时够用)
3.更换二值化阈值多次解析
    /**
     * 解析二维码
     *
     * @param url 图片地址
     * @return 解析失败时返回null
     */
    public static Result decode(String url, boolean handle) {
        try {
            BufferedImage image = ImageIO.read(new File(url));
            if (image != null) {
                int[][] pointGray = new int[image.getWidth()][image.getHeight()];
                if (handle) {
                    image = gray(image, pointGray);
                    Result result = decode(image);
                    String content = result == null ? null : result.getText();
                    if (!StringUtils.isEmpty(content)) {
                        log.debug("The img decode success by only gray,[url:{}]", url);
                        return result;
                    }
                    int threshold = 170;
                    // 更换阈值多次解析
                    for (int i = 0; i < 80; i += 5) {
                        image = binary(image, pointGray, threshold + i);
                        result = decode(image);
                        content = result == null ? null : result.getText();
                        if (!StringUtils.isEmpty(content)) {
                            log.debug("The img decode success,[url:{}],[threshold:{}]", url, threshold + i);
                            break;
                        }
                    }
                    return result;
                }
                return decode(image);
            }
        } catch (IOException e) {
            log.error("read img error", e);
        }
        return null;
    }

	/**
     * 解析同一张图片的多个二维码
     *
     * @param url 图片地址
     * @return 解析结果,失败时返回空数组
     */
    public static Result[] decodeMulti(String url, boolean handle) {
        try {
            BufferedImage image = ImageIO.read(new File(url));
            if (image != null) {
                int[][] pointGray = new int[image.getWidth()][image.getHeight()];
                if (handle) {
                    image = gray(image, pointGray);
                    Result[] results = decodeMulti(image);
                    if (results.length > 0) {
                        log.debug("The img decode success by only gray,[url:{}]", url);
                        return results;
                    }
                    int threshold = 170;
                    // 更换阈值多次解析
                    for (int i = 0; i < 80; i += 5) {
                        image = binary(image, pointGray, threshold + i);
                        results = decodeMulti(image);
                        if (results.length > 0) {
                            log.debug("The img decode success,[url:{}],[threshold:{}]", url, threshold + i);
                            break;
                        }
                    }
                    return results;
                }
                return decodeMulti(image);
            }
        } catch (IOException e) {
            log.error("read img error", e);
        }
        return new Result[0];
    }

    private static Result decode(BufferedImage image) {
        try {
            BufferedImageLuminanceSource source = new BufferedImageLuminanceSource(image);
            BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(source));
            return new MultiFormatReader().decode(bitmap, DECODE_HINTS);
        } catch (NotFoundException ignored) {
        }
        return null;
    }

    private static Result[] decodeMulti(BufferedImage image) {
        try {
            BufferedImageLuminanceSource source = new BufferedImageLuminanceSource(image);
            BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(source));
            return new QRCodeMultiReader().decodeMultiple(bitmap, DECODE_HINTS);
        } catch (NotFoundException ignored) {
        }
        return new Result[0];
    }

    /**
     * 加权灰度化
     *
     * @param image 待处理图片
     * @return 灰度后的图片
     */
    public static BufferedImage gray(BufferedImage image, int[][] pointGray) {
        int width = image.getWidth();
        int height = image.getHeight();
        BufferedImage grayImage = new BufferedImage(width, height, image.getType());
        for (int i = 0; i < width; i++) {
            for (int j = 0; j < height; j++) {
                final int color = image.getRGB(i, j);
                final int r = (color >> 16) & 0xff;
                final int g = (color >> 8) & 0xff;
                final int b = color & 0xff;
                int gray = (int) (0.3 * r + 0.59 * g + 0.11 * b);
                pointGray[i][j] = gray;
                int newPixel = colorToRgb(gray, gray, gray);
                grayImage.setRGB(i, j, newPixel);
            }
        }
        return grayImage;
    }

    private static int colorToRgb(int red, int green, int blue) {
        int newPixel = 0;
        newPixel += 255;
        newPixel = newPixel << 8;
        newPixel += red;
        newPixel = newPixel << 8;
        newPixel += green;
        newPixel = newPixel << 8;
        newPixel += blue;
        return newPixel;
    }

    /**
     * 二值化
     *
     * @param image     原图片
     * @param threshold 阈值
     */
    public static BufferedImage binary(BufferedImage image, int[][] pointGray, int threshold) {
        int width = image.getWidth();
        int height = image.getHeight();
        BufferedImage target = new BufferedImage(width, height, BufferedImage.TYPE_BYTE_BINARY);
        for (int x = 0; x < width; x++) {
            for (int y = 0; y < height; y++) {
                // 自己+周围8个点的相对灰度值
                int i = avgColor(pointGray, x, y, width, height);
                if (i > threshold) {
                    target.setRGB(x, y, Color.WHITE.getRGB());
                } else {
                    target.setRGB(x, y, Color.BLACK.getRGB());
                }
            }
        }
        return target;
    }

    public static int avgColor(int[][] gray, int x, int y, int w, int h) {
        int rs = gray[x][y]
            + (x == 0 ? 255 : gray[x - 1][y])
            + (x == 0 || y == 0 ? 255 : gray[x - 1][y - 1])
            + (x == 0 || y == h - 1 ? 255 : gray[x - 1][y + 1])
            + (y == 0 ? 255 : gray[x][y - 1])
            + (y == h - 1 ? 255 : gray[x][y + 1])
            + (x == w - 1 ? 255 : gray[x + 1][y])
            + (x == w - 1 || y == 0 ? 255 : gray[x + 1][y - 1])
            + (x == w - 1 || y == h - 1 ? 255 : gray[x + 1][y + 1]);
        return rs / 9;
    }
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