diff --git a/AlgorithmModule/include/CameraCheckAnalysisy.hpp b/AlgorithmModule/include/CameraCheckAnalysisy.hpp
index 5321767..f566b4a 100644
--- a/AlgorithmModule/include/CameraCheckAnalysisy.hpp
+++ b/AlgorithmModule/include/CameraCheckAnalysisy.hpp
@@ -188,6 +188,9 @@ private:
 
     int GetLine(const cv::Mat &img, std::vector<cv::Point> &pointList, int lineNum, int xory, int &outP);
 
+    // 找到产品(亮色区域)所在的第一行(顶部边缘), 用于左右图上下对齐
+    int GetProductFirstRow(const cv::Mat &img, int &outRow);
+
 public:
     // 运行的基本参数
     RunInfoST m_RunConfig;
diff --git a/AlgorithmModule/src/CameraCheckAnalysisy.cpp b/AlgorithmModule/src/CameraCheckAnalysisy.cpp
index 68ef754..e271108 100644
--- a/AlgorithmModule/src/CameraCheckAnalysisy.cpp
+++ b/AlgorithmModule/src/CameraCheckAnalysisy.cpp
@@ -9,6 +9,7 @@
 #include "CameraCheckAnalysisy.hpp"
 #include "CheckUtil.hpp"
 #include "Define.h"
+#include <algorithm>
 
 CameraCheckAnalysisy::CameraCheckAnalysisy()
 {
@@ -174,19 +175,52 @@ int CameraCheckAnalysisy::Detect_Pre()
 		m_pdetlog->AddCheckstr(PrintLevel_1, "Detect_Pre", "Cam   %s ==================img size/type != img_B ", strBasic.c_str());
 		return 1;
 	}
+	cv::Mat &img = pImageResult->result->in_shareImage->img;
+	cv::Mat &img_B = pImageResult->result->in_shareImage->img_B;
+
+	// 左右图存在上下错位: 找到左右图产品所在的第一行, 进行简单上下对齐
+	{
+		int rowLeft = -1;
+		int rowRight = -1;
+		if (GetProductFirstRow(img, rowLeft) == 0 && GetProductFirstRow(img_B, rowRight) == 0)
+		{
+			// 以较高的顶边为基准, 把较低的那张图向上平移, 使两图顶边对齐
+			int refRow = std::min(rowLeft, rowRight);
+			int shiftLeft = refRow - rowLeft;	// <= 0, 负值表示向上平移
+			int shiftRight = refRow - rowRight; // <= 0
+
+			m_pdetlog->AddCheckstr(PrintLevel_1, "Detect_Pre", "Cam   %s ==================align rowLeft %d rowRight %d shiftLeft %d shiftRight %d",
+								   strBasic.c_str(), rowLeft, rowRight, shiftLeft, shiftRight);
+
+			if (shiftLeft < 0)
+			{
+				cv::Mat M = (cv::Mat_<double>(2, 3) << 1, 0, 0, 0, 1, (double)shiftLeft);
+				cv::warpAffine(img, img, M, img.size(), cv::INTER_NEAREST, cv::BORDER_CONSTANT, cv::Scalar(0));
+			}
+			if (shiftRight < 0)
+			{
+				cv::Mat M = (cv::Mat_<double>(2, 3) << 1, 0, 0, 0, 1, (double)shiftRight);
+				cv::warpAffine(img_B, img_B, M, img_B.size(), cv::INTER_NEAREST, cv::BORDER_CONSTANT, cv::Scalar(0));
+			}
+		}
+		else
+		{
+			m_pdetlog->AddCheckstr(PrintLevel_1, "Detect_Pre", "Cam   %s ==================GetProductFirstRow fail, skip align", strBasic.c_str());
+		}
+	}
+
 	const int overlap = 1056;
-	if (pImageResult->result->in_shareImage->img.cols <= overlap)
+	if (img.cols <= overlap)
 	{
 		m_pdetlog->AddCheckstr(PrintLevel_1, "Detect_Pre", "Cam   %s ==================img.cols <= overlap %d ", strBasic.c_str(), overlap);
 		return 1;
 	}
 	cv::Mat merge_img;
-	cv::hconcat(pImageResult->result->in_shareImage->img(cv::Rect(0, 0, pImageResult->result->in_shareImage->img.cols - overlap, pImageResult->result->in_shareImage->img.rows)),
-				pImageResult->result->in_shareImage->img_B, merge_img);
-	pImageResult->result->in_shareImage->img = merge_img;
+	cv::hconcat(img(cv::Rect(0, 0, img.cols - overlap, img.rows)), img_B, merge_img);
+	img = merge_img;
 
 	// 拼接完成后 img_B 不再需要，立即释放内存
-	pImageResult->result->in_shareImage->img_B.release();
+	img_B.release();
 
 	if (pImageResult->result->in_shareImage->Det_Mode == DET_MODE_MergeImg)
 	{
@@ -1519,3 +1553,79 @@ int CameraCheckAnalysisy::GetLine(const cv::Mat &img, std::vector<cv::Point> &po
 
 	return 0;
 }
+
+// 找到图像中产品(亮色区域)所在的第一行(顶部边缘), 用于左右图上下对齐
+// 从上往下逐行扫描, 当某一行亮像素数量超过阈值比例时, 认为该行是产品顶边
+int CameraCheckAnalysisy::GetProductFirstRow(const cv::Mat &img, int &outRow)
+{
+	outRow = -1;
+	if (img.empty())
+	{
+		return 1;
+	}
+
+	cv::Mat gray;
+	if (img.channels() == 1)
+	{
+		gray = img;
+	}
+	else if (img.channels() == 3)
+	{
+		cv::cvtColor(img, gray, cv::COLOR_BGR2GRAY);
+	}
+	else
+	{
+		return 1;
+	}
+
+	const uchar brightThreshold = 35;								// 亮像素灰度阈值(与背景判断阈值保持一致)
+	const int needBrightCount = std::max(1, (int)(gray.cols * 0.2)); // 该行亮像素数量占比超过 20% 认为是产品所在行
+	const int rowStep = 16;											// 跳行扫描步长
+
+	// 判断某一行是否为产品所在行(亮像素数量达到阈值)
+	auto isProductRow = [&](int row) -> bool
+	{
+		const uchar *p = gray.ptr<uchar>(row);
+		int brightCount = 0;
+		for (int col = 0; col < gray.cols; ++col)
+		{
+			if (p[col] >= brightThreshold)
+			{
+				if (++brightCount >= needBrightCount)
+				{
+					return true;
+				}
+			}
+		}
+		return false;
+	};
+
+	// 1、跳行粗扫: 每隔 rowStep 行扫描一次, 定位产品顶边的大致位置
+	int rowFound = -1;
+	for (int row = 0; row < gray.rows; row += rowStep)
+	{
+		if (isProductRow(row))
+		{
+			rowFound = row;
+			break;
+		}
+	}
+
+	if (rowFound < 0)
+	{
+		return 2; // 未找到产品顶边
+	}
+
+	// 2、在上一个采样行与 rowFound 之间逐行精确定位
+	int rowStart = std::max(0, rowFound - rowStep + 1);
+	for (int row = rowStart; row <= rowFound; ++row)
+	{
+		if (isProductRow(row))
+		{
+			outRow = row;
+			return 0;
+		}
+	}
+
+	return 2; // 理论上不会走到这里
+}