diff --git a/hgdriver/ImageProcess/ImageApplyOutHole.cpp b/hgdriver/ImageProcess/ImageApplyOutHole.cpp
index 888fa96..926f872 100644
--- a/hgdriver/ImageProcess/ImageApplyOutHole.cpp
+++ b/hgdriver/ImageProcess/ImageApplyOutHole.cpp
@@ -6,6 +6,8 @@
 #include "Device/filetools.h"
 #endif // LOG
 
+//#define DRAW_PIC
+
 CImageApplyOutHole::CImageApplyOutHole(void)
 	: CImageApply()
 	, m_borderSize(20)
@@ -76,14 +78,20 @@ void CImageApplyOutHole::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
 	cv::Mat front_thre, back_thre;
 	hg::threshold_Mat(front, front_thre, m_threshold);
 	hg::threshold_Mat(back, back_thre, m_threshold);
-	//cv::imwrite("front_thre.jpg", front_thre);
-	//cv::imwrite("back_thre.jpg", back_thre);
+
+#ifdef DRAW_PIC
+	cv::imwrite("front_thre.jpg", front_thre);
+	cv::imwrite("back_thre.jpg", back_thre);
+#endif
 
 	cv::Mat element = getStructuringElement(cv::MORPH_RECT, cv::Size(5 * resize_scale, 1));
 	cv::morphologyEx(front_thre, front_thre, cv::MORPH_OPEN, element, cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar::all(0));
 	cv::morphologyEx(back_thre, back_thre, cv::MORPH_OPEN, element, cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar::all(0));
-	//cv::imwrite("front_thre2.jpg", front_thre);
-	//cv::imwrite("back_thre2.jpg", back_thre);
+
+#ifdef DRAW_PIC
+	cv::imwrite("front_thre2.jpg", front_thre);
+	cv::imwrite("back_thre2.jpg", back_thre);
+#endif
 
 	//反面二值化图像水平翻转
 	cv::flip(back_thre, back_thre, 1);  //1:Horizontal
@@ -94,22 +102,22 @@ void CImageApplyOutHole::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
 	hg::findContours(front_thre.clone(), contours_front, b1_front, cv::RETR_CCOMP);
 	hg::findContours(back_thre.clone(), contours_back, b1_back, cv::RETR_CCOMP);
 
-	//提取正反面图像最大轮廓
-	for (size_t i = 0; i < contours_front.size(); i++)
-		if (contours_front[i].size() < MIN_CONTOUR_SIZE)
-		{
-			contours_front.erase(contours_front.begin() + i);
-			b1_front.erase(b1_front.begin() + i);
-			i--;
-		}
+	////提取正反面图像最大轮廓
+	//for (size_t i = 0; i < contours_front.size(); i++)
+	//	if (contours_front[i].size() < MIN_CONTOUR_SIZE)
+	//	{
+	//		contours_front.erase(contours_front.begin() + i);
+	//		b1_front.erase(b1_front.begin() + i);
+	//		i--;
+	//	}
 
-	for (size_t i = 0; i < contours_back.size(); i++)
-		if (contours_back[i].size() < MIN_CONTOUR_SIZE)
-		{
-			contours_back.erase(contours_back.begin() + i);
-			b1_back.erase(b1_back.begin() + i);
-			i--;
-		}
+	//for (size_t i = 0; i < contours_back.size(); i++)
+	//	if (contours_back[i].size() < MIN_CONTOUR_SIZE)
+	//	{
+	//		contours_back.erase(contours_back.begin() + i);
+	//		b1_back.erase(b1_back.begin() + i);
+	//		i--;
+	//	}
 
 	std::vector<cv::Point> maxContour_front = hg::getMaxContour(contours_front, b1_front);
 	std::vector<cv::Point> maxContour_back = hg::getMaxContour(contours_back, b1_back);
@@ -132,26 +140,41 @@ void CImageApplyOutHole::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
 
 	cv::Mat roiMat_front(front_thre, roi_front);                             //在正面二值图像中截取重叠部分
 	cv::Mat roiMat_back(back_thre, roi_back);                                //在反面二值图像中截取重叠部分
-	//cv::imwrite("roiMat_front.jpg", roiMat_front);
-	//cv::imwrite("roiMat_back.jpg", roiMat_back);
+
+#ifdef DRAW_PIC
+	cv::imwrite("roiMat_front.jpg", roiMat_front);
+	cv::imwrite("roiMat_back.jpg", roiMat_back);
+#endif
 
 	//正反面二值图像做或运算，真正镂空区域保留0，其他地方填充为255
 	cv::Mat mask;
 	cv::bitwise_or(roiMat_front, roiMat_back, mask);                            //或运算，正反面二值图像重叠
-	//cv::imwrite("mask1.jpg", mask);
+
+#ifdef DRAW_PIC
+	cv::imwrite("mask1.jpg", mask);
+#endif
 
 	//二值图像重叠图像颜色取反，膨胀，提取轮廓
 	cv::bitwise_not(mask, mask);
-	//cv::imwrite("mask2.jpg", mask);									//反色
+
+#ifdef DRAW_PIC
+	cv::imwrite("mask2.jpg", mask);									//反色
+#endif
 
 	//为了避免孔洞彻底贯穿纸边，人为绘制纸张轮廓，确保所有孔洞为封闭图形，不会与背景粘连
 	cv::polylines(mask, hg::getVertices(mask_rotatedRect), true, cv::Scalar(0), LINE_WIDTH * resize_scale);                         //绘制纸张矩形边缘
-	//cv::imwrite("mask3.jpg", mask);
+
+#ifdef DRAW_PIC
+	cv::imwrite("mask3.jpg", mask);
+#endif
 
 	//膨胀算法，增大孔洞连通区域面积
 	element = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(DILATE_SIZE * resize_scale, DILATE_SIZE * resize_scale));
 	cv::dilate(mask, mask, element, cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar(255));
-	//cv::imwrite("mask4.jpg", mask);
+
+#ifdef DRAW_PIC
+	cv::imwrite("mask4.jpg", mask);
+#endif
 
 	//提取重叠图像轮廓
 	std::vector<std::vector<cv::Point>> contours_mask;
diff --git a/hgdriver/ImageProcess/ImageApplyOutHole.h b/hgdriver/ImageProcess/ImageApplyOutHole.h
index b028f8c..1d3dd49 100644
--- a/hgdriver/ImageProcess/ImageApplyOutHole.h
+++ b/hgdriver/ImageProcess/ImageApplyOutHole.h
@@ -25,7 +25,8 @@
  *				 2022/09/16 v1.9   优化内存消耗
  *				 2022/09/16 v1.9.1 修复缩放比例的逻辑错误。
  *				 2022/11/17 v1.9.2 修复寻找孔洞轮廓BUG。
- * 版本号：v1.9.2
+ *				 2023/05/16 v1.9.3 修复提取纸张最大轮廓的逻辑BUG。
+ * 版本号：v1.9.3
 
  * ====================================================
  */