Java识别条形码的方式
条形码是一种用于识别商品信息的编码标识，常见于超市商品、快递包裹等领域。在Java中，我们可以利用各种库和API来实现条形码的识别。今天我们将介绍几种常见的Java识别条形码的方式，并附上代码示例。
1. 使用ZXing库
ZXing是一个开源的条形码扫描库，支持多种条形码类型，包括二维码和一维码。我们可以通过引入ZXing库来实现条形码的识别。
代码示例
import com.google.zxing.BinaryBitmap;
import com.google.zxing.DecodeHintType;
import com.google.zxing.MultiFormatReader;
import com.google.zxing.ReaderException;
import com.google.zxing.Result;
import com.google.zxing.common.HybridBinarizer;
import com.google.zxing.client.j2se.BufferedImageLuminanceSource;
import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
public class BarcodeReader {
public static void main(String[] args) {
try {
File file = new File("barcode.png");
BufferedImage image = ImageIO.read(file);
BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(new BufferedImageLuminanceSource(image)));
Result result = new MultiFormatReader().decode(bitmap, new HashMap<DecodeHintType, Object>());
System.out.println("Barcode content: " + result.getText());
} catch (IOException | ReaderException e) {
e.printStackTrace();
}
}
}
2. 使用ZBar库
ZBar是另一个流行的开源条形码扫描库，支持多种平台和多种编程语言，包括Java。我们可以通过引入ZBar库来实现条形码的识别。
代码示例
import net.sourceforge.zbar.ImageScanner;
import net.sourceforge.zbar.Image;
import net.sourceforge.zbar.Symbol;
import net.sourceforge.zbar.SymbolSet;
import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
public class BarcodeReader {
public static void main(String[] args) {
try {
ImageScanner scanner = new ImageScanner();
scanner.setConfig(0, 0, 0);
File file = new File("barcode.png");
BufferedImage image = ImageIO.read(file);
Image barcode = new Image(image.getWidth(), image.getHeight(), "Y800");
barcode.setData(image.getRGB(0, 0, image.getWidth(), image.getHeight(), null, 0, image.getWidth()));
int result = scanner.scanImage(barcode);
if (result != 0) {
SymbolSet syms = scanner.getResults();
for (Symbol sym : syms) {
System.out.println("Barcode content: " + sym.getData());
}
}
} catch (IOException e) {
e.printStackTrace();
}
}
}
3. 使用OpenCV库
OpenCV是一个流行的计算机视觉库，支持图像处理和模式识别。我们可以结合OpenCV来实现条形码的识别。
代码示例
import org.opencv.core.Mat;
import org.opencv.core.MatOfByte;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.core.CvType;
import org.opencv.core.MatOfInt;
import org.opencv.core.Point;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Rect;
import org.opencv.core.MatOfRect;
import org.opencv.objdetect.CascadeClassifier;
import java.util.List;
public class BarcodeReader {
public static void main(String[] args) {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
Mat image = Imgcodecs.imread("barcode.png");
Mat gray = new Mat();
Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(gray, gray, 128, 255, Imgproc.THRESH_BINARY);
List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(gray, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);
for (int i = 0; i < contours.size(); i++) {
MatOfPoint contour = contours.get(i);
MatOfPoint2f approxCurve = new MatOfPoint2f();
MatOfPoint2f contour2f = new MatOfPoint2f(contour.toArray());
double approxDistance = Imgproc.arcLength(contour2f, true) * 0.02;
Imgproc
