Key steps and techniques for identifying the authenticity of official contract seals using Java

Key steps and techniques for identifying the authenticity of official contract seals in Java

Overview:
With the continuous development of technology, electronic contracts are gradually replacing traditional paper contracts Quality contracts have become mainstream. However, there are certain risks in the circulation process of electronic contracts, one of which is the authentication of the official seal of the contract. This article will introduce the key steps and techniques to use Java language to identify the authenticity of the official contract seal, and give code examples.

1. Image collection
First, you need to obtain the image information of the contract through a Java program. You can use Java image processing libraries, such as OpenCV, etc., to realize the collection and preprocessing of contract images. During the acquisition process, you can consider adjusting parameters such as brightness, contrast, and sharpness of the image to improve the accuracy of subsequent processing.

The following is a simple sample code that demonstrates how to use the OpenCV library to collect contract images:

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.core.CvType;

public class ContractImageCapture {
    public static void main(String[] args) {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        // 打开摄像头
        VideoCapture capture = new VideoCapture(0);
        if (!capture.isOpened()) {
            System.out.println("无法打开摄像头");
            return;
        }

        Mat mat = new Mat();
        capture.read(mat);

        // 保存图像
        Imgcodecs.imwrite("contract.jpg", mat);

        // 释放摄像头
        capture.release();

        System.out.println("合同图像采集成功");
    }
}

2. Official seal extraction
After obtaining the contract image, the next step is to extract the contract image from the image Extract the official seal from the office. You can use image processing libraries to preprocess images, such as grayscale, binarization, noise reduction and other operations. Then, official seal recognition algorithms, such as methods based on contour or feature matching, can be used to extract the official seal from the processed image.

The following is a simple sample code that demonstrates how to use the OpenCV library to extract the official seal from the contract image:

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.core.CvType;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.imgproc.Imgproc;

public class SealExtraction {
    public static void main(String[] args) {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        String inputImagePath = "contract.jpg";

        // 加载合同图像
        Mat image = Imgcodecs.imread(inputImagePath);

        // 灰度化
        Mat gray = new Mat();
        Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

        // 二值化
        Mat binary = new Mat();
        Imgproc.threshold(gray, binary, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU);

        // 降噪
        Mat denoised = new Mat();
        Imgproc.medianBlur(binary, denoised, 5);

        // 提取公章
        // TODO: 公章识别算法实现

        // 保存公章图像
        String outputImagePath = "seal.jpg";
        Imgcodecs.imwrite(outputImagePath, seal);

        System.out.println("公章提取成功");
    }
}

3. Authenticity Identification
After successfully extracting the official seal image, The next step is to authenticate the authenticity. This step can use image recognition or feature matching methods to determine whether the official seal has been tampered with. Commonly used methods include calculating hash values ​​of images, shape matching, or texture analysis.

The following is a sample code that uses the OpenCV library to calculate image similarity and determine whether the official seal has been tampered with:

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.core.CvType;
import org.opencv.imgproc.Imgproc;

public class SealForgeryDetection {
    public static void main(String[] args) {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        String originalSealPath = "original_seal.jpg";
        String forgedSealPath = "forged_seal.jpg";

        // 加载原始公章图像
        Mat originalSeal = Imgcodecs.imread(originalSealPath);
        // 加载篡改后的公章图像
        Mat forgedSeal = Imgcodecs.imread(forgedSealPath);

        // 计算图像相似度
        double similarity = calculateSimilarity(originalSeal, forgedSeal);
        double threshold = 0.9; // 设定相似度的阈值

        if (similarity >= threshold) {
            System.out.println("公章真品");
        } else {
            System.out.println("公章伪品");
        }
    }

    private static double calculateSimilarity(Mat image1, Mat image2) {
        // TODO: 图像相似度计算算法实现
        return 0.0;
    }
}

Conclusion:
Through the above steps, we can use Java language to implement the contract The function of identifying the authenticity of official seals. Of course, the accuracy of authenticity identification depends on the design and implementation of image processing and recognition algorithms. We can debug and optimize according to actual needs to improve the accuracy and reliability of verification results.

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