twain3.0/huagao/ImageProcess/ImageApplyDiscardBlank.cpp

#include "ImageApplyDiscardBlank.h"
#include "ImageProcess_Public.h"

CImageApplyDiscardBlank::CImageApplyDiscardBlank()
	: m_res(false)
	, m_dSize(20)
	, m_devTh(15, 15, 15, 15)
{
}

CImageApplyDiscardBlank::CImageApplyDiscardBlank(int blockSize, int devTh)
	: m_res(false)
	, m_dSize(blockSize)
	, m_devTh(devTh)
{
}

CImageApplyDiscardBlank::CImageApplyDiscardBlank(bool isnormal)
	: m_res(false)
	, m_isNormalDiscard(isnormal)
{
	m_dSize = m_isNormalDiscard ? 200 : 300;
	m_devTh = m_isNormalDiscard ? cv::Scalar::all(8) : cv::Scalar::all(20);
}

CImageApplyDiscardBlank::~CImageApplyDiscardBlank(void)
{
}

int CImageApplyDiscardBlank::processRectR(const cv::Mat& image, cv::RotatedRect& rotatedRect, std::vector<cv::Point>& maxContour,
	double scale, double thresh, int blobAreaSize)
{
	cv::Mat gray;
	int blockCount = 0;
	if (image.channels() == 3)
		if (scale != 1.0f)
		{
			cv::Size ResImgSiz = cv::Size(image.cols * scale, image.rows * scale);
			resize(image, gray, cv::Size(), scale, scale, 0);
			cvtColor(gray, gray, CV_BGR2GRAY);
		}
		else
			cvtColor(image, gray, CV_BGR2GRAY);
	else
		if (scale != 1.0f)
			resize(image, gray, cv::Size(), scale, scale, 0);
		else
			gray = image;

	cv::Mat threshold_img;
	threshold(gray, threshold_img, thresh, 255.0, CV_THRESH_BINARY);
	std::vector<std::vector<cv::Point>> contours;
	std::vector<cv::Vec4i> h1;
	hg::findContours(threshold_img, contours, h1, CV_CHAIN_APPROX_SIMPLE);
	threshold_img.release();

	if (contours.size() == 0)
		return blockCount;

	std::vector<cv::Point2f> list_com;
	for (int i = 0; i < contours.size(); i++)
	{
		double area = cv::contourArea(contours[i]);
		if (area > blobAreaSize)
		{
			blockCount++;
			for (int j = 0; j < contours[i].size(); j++)
				list_com.push_back(contours[i][j]);
		}
	}

	if (list_com.size() == 0)
		return blockCount;

	rotatedRect = cv::minAreaRect(list_com);
	rotatedRect.center.x /= (float)scale;
	rotatedRect.center.y /= (float)scale;
	rotatedRect.size.width /= (float)scale;
	rotatedRect.size.height /= (float)scale;

	if (rotatedRect.angle < -45.0f)
	{
		rotatedRect.angle += 90.0f;
		float l_temp = rotatedRect.size.width;
		rotatedRect.size.width = rotatedRect.size.height;
		rotatedRect.size.height = l_temp;
	}
	if (rotatedRect.angle > 45.0f)
	{
		rotatedRect.angle -= 90.0f;
		float l_temp = rotatedRect.size.width;
		rotatedRect.size.width = rotatedRect.size.height;
		rotatedRect.size.height = l_temp;
	}

	std::vector<int> hull(list_com.size());
	cv::convexHull(list_com, hull);

	for (int i = 0; i < hull.size(); i++)
	{
		cv::Point temp = list_com[hull[i]];
		int x = (int)(temp.x / scale);
		int y = (int)(temp.y / scale);
		maxContour.push_back(cv::Point(x, y));
	}

	return blockCount;
}

bool CImageApplyDiscardBlank::scalar_LE(const cv::Scalar& val1, const cv::Scalar& val2)
{
	for (int i = 0; i < 3; i++)
		if (val1[i] > val2[i])
			return false;
	return true;
}

void CImageApplyDiscardBlank::setIntensity(int val)
{
	val = cv::max(cv::min(100, val), 2);
	m_devTh = cv::Scalar::all(val);
}

cv::Mat CImageApplyDiscardBlank::getRoiMat(const cv::Mat& image)
{
	int gap = 100;
	cv::RotatedRect rect;
	std::vector<cv::Point> contour;
	double scale = 0.25;
	double thresh = 50;
	int blobSize = 200;
	processRectR(image, rect, contour, scale, thresh, blobSize);
	cv::Rect rect2 = rect.boundingRect();
	cv::Rect inRect = rect2 & cv::Rect(0, 0, image.cols, image.rows);
	gap = cv::max(inRect.width - rect.size.width, inRect.height - rect.size.height) + 100;
	inRect = cv::Rect(inRect.x + gap, inRect.y + gap, inRect.width - gap * 2, inRect.height - gap * 2);

	if (inRect.width <= 0 || inRect.height <= 0)
		return cv::Mat();
	return image(inRect);
}

void CImageApplyDiscardBlank::apply(cv::Mat& pDib, int side)
{
#ifdef LOG
	FileTools::write_log("imgprc.txt", "enter CImageApplyDiscardBlank apply");
#endif // LOG

	if (pDib.empty())
	{
#ifdef LOG
		FileTools::write_log("imgprc.txt", "exit CImageApplyDiscardBlank apply");
#endif // LOG
		return;
	}

	cv::Scalar mean;
	cv::Scalar dev;
	cv::Mat image = getRoiMat(pDib);
	cv::Rect rect;
	cv::Rect imRect(0, 0, image.cols, image.rows);
	for (int i = 0; i < image.cols; i += m_dSize)
		for (int j = 0; j < image.rows; j += m_dSize)
		{
			rect = cv::Rect(i, j, m_dSize, m_dSize) & imRect;
			if (rect != cv::Rect())
			{
				cv::meanStdDev(image(rect), mean, dev);
				if (!scalar_LE(dev, m_devTh))
				{
					m_res = false;
#ifdef LOG
					FileTools::write_log("imgprc.txt", "exit CImageApplyDiscardBlank apply");
#endif // LOG
					return;
				}
			}
		}
	m_res = true;
	if (m_res)
		pDib.release();
#ifdef LOG
	FileTools::write_log("imgprc.txt", "exit CImageApplyDiscardBlank apply");
#endif // LOG
}

void CImageApplyDiscardBlank::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
{
	(void)isTwoSide;
	int i = 0;
	for (cv::Mat& var : mats) {
		if (i != 0 && isTwoSide == false)
			break;
		if (!var.empty())
			apply(var, 0);
		i++;
	}
}

bool CImageApplyDiscardBlank::apply(const cv::Mat& pDib, int blockSize, int devTh)
{
	if (pDib.empty())
		return true;

	cv::Scalar mean;
	cv::Scalar dev;
	cv::Scalar s_devTh = cv::Scalar::all(devTh);
	cv::Mat image = getRoiMat(pDib);
	if (image.empty())
		return false;
	cv::Rect rect;
	cv::Rect imRect(0, 0, image.cols, image.rows);
	for (int i = 0; i < image.cols; i += blockSize)
		for (int j = 0; j < image.rows; j += blockSize)
		{
			rect = cv::Rect(i, j, blockSize, blockSize) & imRect;
			if (rect != cv::Rect())
			{
				cv::meanStdDev(image(rect), mean, dev);
				if (!scalar_LE(dev, s_devTh))
					return false;
			}
		}
	return true;
}