How to use Java technology to identify the authenticity of the official seal in a contract

How to use Java technology to identify the authenticity of the official seal in a contract

Abstract:
The official seal plays an important role in the contract to ensure the legality and Authenticity. However, the technology for forging official seals is also constantly updated, posing challenges to contract identification. This article will introduce how to use Java technology to identify the authenticity of the official seal in a contract, and give corresponding code examples.

1. The principle of identifying the authenticity of the official seal
The official seal is the legal seal of enterprises and institutions, and it is unique, closed and normative. The authenticity of an official seal can be identified through the following aspects:

1. Visual characteristics: The appearance of an official seal has certain specifications, including seal patterns, fonts, seal edges, etc. Forged official seals usually differ in the details.
2. Material characteristics: Official seals are usually made of special materials such as metal or stone, and have certain characteristics in texture and weight.
3. Seal Engraving: The text on the official seal is usually embossed and anti-counterfeiting, including tiny details that are difficult to distinguish with the naked eye.
4. Seal laser features: Laser marking or laser engraving is often used in the anti-counterfeiting technology of official seals, which will display specific patterns under specific light sources.

2. How to identify the authenticity of the official seal using Java technology

1. Image processing technology
   Through the Java image processing library, the official seal image in the contract can be processed and analysis. You can use libraries such as OpenCV and JavaCV to extract visual features of official seals, such as edge recognition, contour detection, etc. According to the standard official seal style, judge whether the official seal complies with the regulations, so as to identify the authenticity.

Code example:
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;
import org.opencv.core.CvType;
import org.opencv.core.CvType.CV_8U;

public class SealDetection {
public static void main(String[] args) {

  // 加载本地库
  System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
  
  // 读取图片文件
  Mat sourceImage = Imgcodecs.imread("contract_seal.jpg");
  
  // 灰度处理
  Mat grayImage = new Mat();
  Imgproc.cvtColor(sourceImage, grayImage, Imgproc.COLOR_BGR2GRAY);
  
  // 图像边缘检测
  Mat edgeImage = new Mat();
  Imgproc.Canny(grayImage, edgeImage, 100, 200);
  
  // 圆查找
  Mat circles = new Mat();
  Imgproc.HoughCircles(edgeImage, circles, Imgproc.CV_HOUGH_GRADIENT, 1, edgeImage.rows()/8, 200, 100, 0, 0);
  
  // 绘制检测到的圆
  for (int i = 0; i < circles.cols(); i++) {
     double[] circleData = circles.get(0, i);
     Point center = new Point(Math.round(circleData[0]), Math.round(circleData[1]));
     int radius = (int) Math.round(circleData[2]);
     Imgproc.circle(sourceImage, center, radius, new Scalar(0, 255, 0), 2);
  }
  
  // 显示处理结果
  HighGui.imshow("Detected Seals", sourceImage);
  HighGui.waitKey(0);

}
}

2. Seal image comparison technology
   Use Java's image processing library to first obtain a batch of real official seal images, and then compare the official seal images in the contract with the real ones Official seal images for comparison. Commonly used methods include image feature extraction and similarity calculation, etc. The matching degree is calculated to determine the authenticity of the official seal.

Code example:
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.features2d.FeatureDetector;
import org. opencv.features2d.Features2d;
import org.opencv.features2d.FlannBasedMatcher;
import org.opencv.features2d.KAZE;
import org.opencv.features2d.KeyPoint;
import org.opencv. features2d.DescriptorExtractor;
import org.opencv.features2d.DescriptorMatcher;
import java.util.ArrayList;
import java.util.LinkedList;
import java.util.List;

public class SealValidation {

public static void main(String[] args) {

  //加载本地库
  System.loadLibrary(Core.NATIVE_LIBRARY_NAME); 

  //读取真实公章图像
  Mat refImage = Imgcodecs.imread("real_seal.jpg"); 
  
  //读取合同公章图像
  Mat testImage = Imgcodecs.imread("contract_seal.jpg"); 
  
  //创建KAZE关键点检测器
  FeatureDetector detector = FeatureDetector.create(FeatureDetector.KAZE); 
  
  //检测关键点
  MatOfKeyPoint refKp = new MatOfKeyPoint(); 
  MatOfKeyPoint testKp = new MatOfKeyPoint(); 
  detector.detect(refImage, refKp); 
  detector.detect(testImage, testKp); 
  
  //提取特征描述子
  DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.KAZE); 
  
  Mat descriptorRef = new Mat(); 
  Mat descriptorTest = new Mat(); 
  extractor.compute(refImage, refKp, descriptorRef); 
  extractor.compute(testImage, testKp, descriptorTest); 
  
  //创建FLANN特征匹配器
  DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING); 
  
  //匹配特征描述子
  MatOfDMatch matches = new MatOfDMatch(); 
  matcher.match(descriptorRef, descriptorTest, matches); 
  
  //绘制匹配结果
  Mat outputImage = new Mat(); 
  Scalar matchColor = new Scalar(0, 255, 0); 
  Features2d.drawMatches(refImage, refKp, testImage, testKp, matches, outputImage, matchColor, 
     Scalar.all(-1), new MatOfByte(), 
     Features2d.NOT_DRAW_SINGLE_POINTS); 
  
  //计算匹配度
  double totalMatches = matches.rows(); 
  System.out.println("总匹配点数: " + totalMatches); 
  
  double maxDist = 0; 
  double minDist = 100; 
  List<DMatch> matchList = matches.toList(); 
  
  //获取匹配点的最大和最小距离
  for (int i = 0; i < totalMatches; i++) { 
     double dist = matchList.get(i).distance; 
     if (dist < minDist) minDist = dist; 
     if (dist > maxDist) maxDist = dist; 
  } 
  
  //选择适合的匹配点
  LinkedList<DMatch> goodMatches = new LinkedList<DMatch>(); 
  for (int i = 0; i < totalMatches; i++) { 
     if (matchList.get(i).distance <= 3 * minDist) { 
        goodMatches.addLast(matchList.get(i)); 
     } 
  } 
  
  //计算匹配率
  double matchPercentage = (goodMatches.size() / totalMatches) * 100; 
  System.out.println("公章匹配率: " + matchPercentage + "%"); 
  
  //显示处理结果
  HighGui.imshow("Matched Seals", outputImage); 
  HighGui.waitKey(0); 

}
}

3. Conclusion
Use Java technology Identifying the authenticity of an official seal in a contract is a complex and challenging task. Through image processing and feature matching technology, we can analyze and compare official seals in various dimensions to identify the authenticity of official seals. Of course, as forgery technology continues to change, methods for identifying official seals also need to be constantly updated and improved.

Identification of the authenticity of an official seal is an important link in a contract and is of great significance to both enterprises, institutions and individuals. I hope that the Java technology methods and code examples provided in this article can provide some help to readers in identifying the authenticity of the official seal in the contract.

The above is the detailed content of How to use Java technology to identify the authenticity of the official seal in a contract. For more information, please follow other related articles on the PHP Chinese website!