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+package org.springblade.archive.utils;
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+
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+import org.apache.pdfbox.pdmodel.PDDocument;
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+import org.apache.pdfbox.rendering.PDFRenderer;
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+import org.bytedeco.javacpp.BytePointer;
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+import org.bytedeco.javacv.Frame;
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+import org.bytedeco.javacv.Java2DFrameConverter;
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+import org.bytedeco.javacv.OpenCVFrameConverter;
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+import org.bytedeco.opencv.opencv_core.*;
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+import org.bytedeco.opencv.opencv_imgproc.*;
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+import static org.bytedeco.opencv.global.opencv_core.*;
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+import org.bytedeco.opencv.global.opencv_imgcodecs;
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+import org.opencv.core.CvType;
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+import org.springblade.common.utils.CommonUtil;
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+
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+import java.awt.image.BufferedImage;
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+import java.io.ByteArrayOutputStream;
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+import java.io.File;
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+import java.io.IOException;
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+
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+import static org.bytedeco.opencv.global.opencv_imgcodecs.*;
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+import static org.bytedeco.opencv.global.opencv_imgproc.*;
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+
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+/**
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+ * 简单检测图片质量
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+ */
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+public class ImageQualityDetectorUtils {
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+
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+// public static void main(String[] args) throws IOException {
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+// try (PDDocument document = PDDocument.load(new File("C:\\Users\\泓创02\\Downloads\\73ef17c2f24ea5b83747a1ac5c2c3f0f.pdf"));
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+// Java2DFrameConverter converter1 = new Java2DFrameConverter();
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+// OpenCVFrameConverter.ToMat converter2 = new OpenCVFrameConverter.ToMat();) {
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+// if (document.isEncrypted()) {
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+// throw new RuntimeException("PDF文件已加密，请先解密");
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+// }
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+// // 创建PDF渲染器
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+// PDFRenderer pdfRenderer = new PDFRenderer(document);
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+// // 获取总页数
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+// int pages = document.getNumberOfPages();
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+// for (int i = 0; i < pages; i++) {
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+// Frame frame = converter1.convert(pdfRenderer.renderImageWithDPI(i, 300));
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+// Mat image = converter2.convert(frame);
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+// if (image.empty()) {
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+// System.out.println("无法加载图像");
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+// return;
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+// }
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+// // 检测各种质量问题
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+// boolean hasStains = detectLargeStains(image);
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+// boolean isObstructed = detectTextObstruction(image);
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+// boolean hasShadows = detectShadows(image);
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+//
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+// System.out.println("检测结果:");
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+// System.out.println("大面积污渍: " + (hasStains ? "是" : "否"));
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+// System.out.println("文字遮挡: " + (isObstructed ? "是" : "否"));
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+// System.out.println("黑影/阴影: " + (hasShadows ? "是" : "否"));
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+//
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+// if (hasStains || isObstructed || hasShadows) {
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+// System.out.println("图像质量不佳，建议重新扫描");
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+// } else {
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+// System.out.println("图像质量良好");
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+// }
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+// }
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+// }
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+// }
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+
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+ /**
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+ * 检测图像中是否存在大面积污渍
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+ * @param image 输入图像
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+ * @return 污渍检测结果
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+ */
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+ public static boolean detectLargeStains(Mat image) {
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+ // 转换为灰度图
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+ Mat gray = new Mat();
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+ cvtColor(image, gray, COLOR_BGR2GRAY);
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+
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+ // 应用阈值处理，突出污渍区域
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+ Mat thresh = new Mat();
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+ threshold(gray, thresh, 0, 255, THRESH_BINARY_INV + THRESH_OTSU);
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+
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+ // 形态学操作去除噪声
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+ Mat kernel = getStructuringElement(MORPH_ELLIPSE, new Size(5, 5));
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+ morphologyEx(thresh, thresh, MORPH_OPEN, kernel);
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+
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+ // 查找轮廓
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+ MatVector contours = new MatVector();
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+ findContours(thresh, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
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+
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+ // 检查是否有大面积的污渍
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+ double imageArea = image.rows() * image.cols();
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+ for (int i = 0; i < contours.size(); i++) {
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+ double area = contourArea(contours.get(i));
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+ // 如果污渍面积超过图像面积的5%，则认为存在大面积污渍
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+ if (area > imageArea * 0.05) {
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+ return true;
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+ }
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+ }
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+
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+ return false;
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+ }
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+
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+ /**
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+ * 检测图像中文字是否被遮挡
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+ * @param image 输入图像
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+ * @return 遮挡检测结果
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+ */
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+ public static boolean detectTextObstruction(Mat image) {
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+ // 转换为灰度图
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+ Mat gray = new Mat();
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+ cvtColor(image, gray, COLOR_BGR2GRAY);
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+
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+ // 边缘检测
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+ Mat edges = new Mat();
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+ Canny(gray, edges, 50, 150);
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+
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+ // 形态学操作连接边缘
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+ Mat kernel = getStructuringElement(MORPH_RECT, new Size(3, 3));
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+ morphologyEx(edges, edges, MORPH_CLOSE, kernel);
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+
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+ // 查找轮廓
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+ MatVector contours = new MatVector();
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+ findContours(edges, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
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+
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+ // 分析轮廓特征判断是否有遮挡
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+ for (int i = 0; i < contours.size(); i++) {
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+ Mat contour = contours.get(i);
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+ double area = contourArea(contour);
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+
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+ // 计算轮廓的边界矩形
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+ Rect boundingRect = boundingRect(contour);
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+
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+ // 如果区域较大但边缘不规则，可能是遮挡
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+ if (area > 1000) {
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+ double aspectRatio = (double) boundingRect.width() / boundingRect.height();
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+ if (aspectRatio > 5 || aspectRatio < 0.2) {
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+ return true;
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+ }
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+ }
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+ }
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+ return false;
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+ }
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+
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+ /**
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+ * 检测图像中是否存在黑影或阴影
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+ * @param image 输入图像
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+ * @return 阴影检测结果
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+ */
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+ public static boolean detectShadows(Mat image) {
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+ // 转换为灰度图
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+ Mat gray = new Mat();
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+ cvtColor(image, gray, COLOR_BGR2GRAY);
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+
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+ // 应用高斯模糊减少噪声
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+ Mat blurred = new Mat();
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+ GaussianBlur(gray, blurred, new Size(5, 5), 0);
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+
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+ // 计算图像的梯度
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+ Mat gradX = new Mat();
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+ Mat gradY = new Mat();
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+ Sobel(blurred, gradX, CV_32F, 1, 0);
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+ Sobel(blurred, gradY, CV_32F, 0, 1);
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+
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+ // 计算梯度幅值
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+ Mat gradient = new Mat();
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+ magnitude(gradX, gradY, gradient);
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+
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+ // 转换为8位图像
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+ Mat gradient8u = new Mat();
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+ convertScaleAbs(gradient, gradient8u);
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+
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+ // 应用阈值分割
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+ Mat binary = new Mat();
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+ threshold(gradient8u, binary, 30, 255, THRESH_BINARY);
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+
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+ // 计算阴影区域占比
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+ double totalPixels = binary.rows() * binary.cols();
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+ double shadowPixels = totalPixels - countNonZero(binary);
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+ double shadowRatio = shadowPixels / totalPixels;
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+
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+ // 如果阴影区域超过10%，则认为存在明显阴影
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+ return shadowRatio > 0.1;
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+ }
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+
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+}
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LHB