更新自动颜色识别算法，提高识别率

hgdriver/ImageProcess/ImageApplyColorRecognition.cpp

@@ -1,28 +1,5 @@
 #include "ImageApplyColorRecognition.h"
 
-/// <summary>
-/// 检测图像是否是彩色。当前逻辑仅针对红色像素进行判断，即存在红色像素则为彩色，否则为非彩色
-/// </summary>
-/// <param name="image">待测图像</param>
-/// <returns>true为彩色，false为非彩色</returns>
-bool isColor(const cv::Mat& image, double threshold = 60)
-{
-	if (image.channels() != 3) return false;
-
-	cv::Mat pDib_resize;
-	cv::resize(image, pDib_resize, cv::Size(200, 200), 0, 0, cv::INTER_AREA);
-
-	cv::Mat hsv;
-	cv::cvtColor(pDib_resize, hsv, cv::COLOR_BGR2HSV_FULL);
-	std::vector<cv::Mat> hsv_channels;
-	cv::split(hsv, hsv_channels);
-
-	double minVal, maxVal;
-	cv::minMaxLoc(hsv_channels[1], &minVal, &maxVal);
-
-	return maxVal > threshold;
-}
-
 bool isGray(const cv::Mat& image)
 {
 	//if (image.channels() == 3) return true;
@@ -62,6 +39,7 @@ CImageApplyColorRecognition::~CImageApplyColorRecognition(void)
 {
 }
 
+#define HSV_S_THRE 30
 void CImageApplyColorRecognition::apply(cv::Mat& pDib, int side)
 {
 	if (pDib.channels() != 3)
@@ -69,7 +47,7 @@ void CImageApplyColorRecognition::apply(cv::Mat& pDib, int side)
 		m_result = Gray;
 		return;
 	}
-	m_result = isColor(pDib) ? Color : Gray;
+	m_result = isColor(pDib, HSV_S_THRE) ? Color : Gray;
 	if (m_result == Gray && pDib.channels() == 3)
 		cv::cvtColor(pDib, pDib, cv::COLOR_BGR2GRAY);
 
@@ -135,3 +113,26 @@ std::vector<CImageApplyColorRecognition::ColorType> CImageApplyColorRecognition:
 {
 	return m_results;
 }
+
+/// <summary>
+/// 检测图像是否是彩色。当前逻辑仅针对红色像素进行判断，即存在红色像素则为彩色，否则为非彩色
+/// </summary>
+/// <param name="image">待测图像</param>
+/// <returns>true为彩色，false为非彩色</returns>
+bool CImageApplyColorRecognition::isColor(const cv::Mat& image, double threshold)
+{
+	if (image.channels() != 3) return false;
+
+	cv::Mat pDib_resize;
+	cv::resize(image, pDib_resize, cv::Size(200, 200), 0, 0, cv::INTER_AREA);
+	//cv::imwrite("pDib_resize.bmp", pDib_resize);
+	cv::Mat hsv;
+	cv::cvtColor(pDib_resize, hsv, cv::COLOR_BGR2HSV_FULL);
+	std::vector<cv::Mat> hsv_channels;
+	cv::split(hsv, hsv_channels);
+
+	double minVal, maxVal;
+	cv::minMaxLoc(hsv_channels[1], &minVal, &maxVal);
+
+	return maxVal > threshold;
+}

hgdriver/ImageProcess/ImageApplyColorRecognition.h

@@ -10,7 +10,8 @@
  *               v1.3    2021/04/19  修改识别策略，能够识别占比1‰的彩色图像。只区分彩色和灰度图。
  *               v1.4    2021/06/18  调整二级色彩区间，从原来的[90, 200]调整为[50, 200]。
  *               v1.5    2023/11/22  调整彩色判定策略。
- * 版本号：v1.5
+ *               v1.5.1  2023//11/28 调整饱和度判定阈值
+ * 版本号：v1.5.1
  * ====================================================
  */
 
@@ -60,6 +61,9 @@ public:
     /// <returns>色彩类型数组</returns>
     std::vector<ColorType> getResults();
 
+private:
+    bool isColor(const cv::Mat& image, double threshold = 30);
+
 private:
     ColorType m_result;
     std::vector<ColorType> m_results;