mirror of http://192.168.1.51:8099/lmh188/twain3.0
修改UVTwain 背景黑色情况下裁切异常问题
This commit is contained in:
lovelyyoung
parent
90f0c0935c
commit
4b729a4585
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@ -1,13 +1,12 @@
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#include "ImageApplyAutoCrop.h"
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#include "ImageProcess_Public.h"
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#define RE 2
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CImageApplyAutoCrop::CImageApplyAutoCrop()
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: m_isCrop(false)
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, m_isDesaskew(false)
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, m_isFillBlank(false)
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, m_isConvexHull(true)
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, m_isFillColor(false)
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, m_threshold(40)
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, m_noise(2)
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, m_indent(5)
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@ -19,6 +18,7 @@ CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFi
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, m_isDesaskew(isDesaskew)
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, m_isFillBlank(isFillBlank)
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, m_isConvexHull(isConvex)
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, m_isFillColor(false)
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, m_threshold(threshold)
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, m_noise(noise)
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, m_indent(indent)
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@ -32,45 +32,27 @@ CImageApplyAutoCrop::~CImageApplyAutoCrop()
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void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side)
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{
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "enter CImageApplyAutoCrop apply");
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#endif // LOG
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if (pDib.empty())
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{
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply");
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#endif // LOG
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return;
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}
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(void)side;
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if (pDib.empty()) return;
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if (!m_isCrop && !m_isDesaskew && !m_isFillBlank && m_fixedSize.empty()) return;
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cv::Mat src = pDib;
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cv::Mat thre;
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cv::Mat dst;
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cv::Mat src_resize;
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cv::resize(src, src_resize, cv::Size(src.cols / RE, src.rows / RE));
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cv::Mat scale_mat;
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cv::Mat thre(src_resize.size(), CV_8UC1);
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hg::threshold_Mat(src_resize, thre, m_threshold);
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src_resize.release();
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hg::threshold_Mat(src, thre, m_threshold);
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if (m_noise > RE)
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if (m_noise > 0)
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{
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cv::Mat element = getStructuringElement(cv::MORPH_RECT, cv::Size(m_noise / RE, m_noise / RE));
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cv::Mat element = getStructuringElement(cv::MORPH_RECT, cv::Size(m_noise, m_noise));
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cv::morphologyEx(thre, thre, cv::MORPH_OPEN, element);
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element.release();
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}
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std::vector<cv::Vec4i> hierarchy;
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std::vector<std::vector<cv::Point>> contours;
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hg::findContours(thre, contours, hierarchy, cv::RETR_EXTERNAL);
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std::vector<cv::Point> maxContour = hg::getMaxContour(contours, hierarchy);
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m_maxContour = hg::getMaxContour(contours, hierarchy);
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for (cv::Point& item : maxContour)
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{
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item.x = item.x * RE - RE / 2;
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item.y = item.y * RE - RE / 2;
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}
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if (maxContour.size() == 0)
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if (m_maxContour.size() == 0)
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{
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thre.release();
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#ifdef LOG
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@ -81,68 +63,83 @@ void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side)
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thre.release();
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dst.release();
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cv::RotatedRect rect = hg::getBoundingRect(maxContour);
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cv::RotatedRect rect = hg::getBoundingRect(m_maxContour);
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m_rect = rect;
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if (m_isDesaskew)
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cv::Rect boudingRect = cv::boundingRect(m_maxContour);
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boudingRect.x -= 1;
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boudingRect.y -= 1;
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boudingRect.width += 2;
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boudingRect.height += 2;
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if (m_isDesaskew && rect.angle != 0)
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{
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cv::Point2f srcTri[4];
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cv::Point2f dstTri[3];
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rect.points(srcTri);
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for (cv::Point2f& p : srcTri)
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{
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p.x -= 0.5;
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p.y -= 0.5;
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}
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dstTri[0] = cv::Point2f(0, rect.size.height - 1);
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dstTri[1] = cv::Point2f(0, 0);
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dstTri[2] = cv::Point2f(rect.size.width - 1, 0);
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cv::Mat warp_mat;
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warp_mat = cv::getAffineTransform(srcTri, dstTri);
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cv::warpAffine(src, dst, warp_mat, rect.size);
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cv::warpAffine(src, dst, warp_mat, rect.size, cv::INTER_NEAREST);
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}
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else
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dst = src(rect.boundingRect() & cv::Rect(0, 0, src.cols, src.rows));
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dst = src(boudingRect & cv::Rect(0, 0, src.cols, src.rows));
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m_maxContour.clear();
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m_maxContour.push_back(cv::Point(-1, dst.rows));
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m_maxContour.push_back(cv::Point(-1, -1));
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m_maxContour.push_back(cv::Point(dst.cols, -1));
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m_maxContour.push_back(cv::Point(dst.cols, dst.rows));
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if (m_isFillBlank)
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{
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cv::Mat thre_dst;
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hg::threshold_Mat(dst, thre_dst, m_threshold);
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cv::erode(thre_dst, thre_dst, cv::Mat(), cv::Point(-1, -1), m_indent);
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if (m_indent > 0)
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{
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std::vector<cv::Point> rectEdge{ cv::Point(0, 0) ,cv::Point(thre_dst.cols - 1, 0),
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cv::Point(thre_dst.cols - 1, thre_dst.rows - 1), cv::Point(0, thre_dst.rows - 1) };
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std::vector<std::vector<cv::Point>> rectEdges{ rectEdge };
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cv::drawContours(thre_dst, rectEdges, 0, cv::Scalar::all(0));
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cv::Mat element = cv::getStructuringElement(cv::MorphShapes::MORPH_RECT, cv::Size(m_indent, m_indent));
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cv::erode(thre_dst, thre_dst, element, cv::Point(-1, -1), 1);
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}
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hierarchy.clear();
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contours.clear();
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maxContour.clear();
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m_maxContour.clear();
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hg::findContours(thre_dst, contours, hierarchy, cv::RETR_EXTERNAL);
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thre_dst.release();
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maxContour = hg::getMaxContour(contours, hierarchy);
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if (m_isConvexHull)
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hg::convexHull(maxContour, maxContour);
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{
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m_maxContour = hg::getMaxContour(contours, hierarchy);
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hg::convexHull(m_maxContour, m_maxContour);
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contours.clear();
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contours.push_back(m_maxContour);
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}
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contours.clear();
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contours.resize(2);
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contours[0] = maxContour;
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contours[1].push_back(cv::Point(0, dst.rows - 1));
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contours[1].push_back(cv::Point(0, 0));
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contours[1].push_back(cv::Point(dst.cols - 1, 0));
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contours[1].push_back(cv::Point(dst.cols - 1, dst.rows - 1));
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contours.push_back(std::vector<cv::Point>());
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contours[contours.size() - 1].push_back(cv::Point(-1, dst.rows - 1));
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contours[contours.size() - 1].push_back(cv::Point(-1, -1));
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contours[contours.size() - 1].push_back(cv::Point(dst.cols, -1));
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contours[contours.size() - 1].push_back(cv::Point(dst.cols, dst.rows));
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hg::fillPolys(dst, contours, cv::Scalar(255, 255, 255));
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hg::fillPolys(dst, contours, m_isFillColor ? getBackGroudColor(pDib, rect.size.area()) : cv::Scalar(255, 255, 255));
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}
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pDib.release();
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if ((m_isCrop && side == 0) || (side == 1 && m_fixedSize.width * m_fixedSize.height == 0))
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{
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if (/*(m_isCrop && side == 0) || (side == 1 && m_fixedSize.width * m_fixedSize.height == 0)*/ m_isCrop)
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pDib = dst.clone();
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dst.release();
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}
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else
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{
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if (m_isCrop && side == 1 && !m_fixedSize.empty())
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if (std::abs(m_fixedSize.width - dst.cols) > 50 || std::abs(m_fixedSize.height - dst.rows) > 50)
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{
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pDib = dst.clone();
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply");
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#endif // LOG
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return;
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}
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pDib = cv::Mat(m_fixedSize, dst.type(), m_isFillBlank ? cv::Scalar(255, 255, 255) : cv::Scalar(0, 0, 0));
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cv::Rect roi;
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@ -151,19 +148,10 @@ void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side)
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roi.y = dst.rows > pDib.rows ? (dst.rows - pDib.rows) / 2 : 0;
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roi.height = cv::min(pDib.rows, dst.rows);
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cv::Rect rect((pDib.cols - roi.width) / 2, (pDib.rows - roi.height) / 2, roi.width, roi.height);
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#if 0
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std::string outrectinfo ="copy to rect x: "+std::to_string(rect.x) + "y: "+std::to_string(rect.y) + "width: "+std::to_string(rect.width) + "height: "+std::to_string(rect.height);
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std::string outroiinfo = "roi x: " + std::to_string(roi.x) + "y: " + std::to_string(roi.y) + "width: " + std::to_string(roi.width) + "height: " + std::to_string(roi.height);
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std::string dstsize = "dst size: width:" + std::to_string(dst.cols) + "height: " + std::to_string(dst.rows);
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std::string pDibszie= "pDib size: width: " + std::to_string(pDib.cols) + "height: " + std::to_string(pDib.rows);
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FileTools::write_log("imgprc.txt", dstsize);
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FileTools::write_log("imgprc.txt", pDibszie);
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FileTools::write_log("imgprc.txt", outrectinfo);
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FileTools::write_log("imgprc.txt", outroiinfo);
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#endif // LOG
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dst(roi).copyTo(pDib(rect));
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dst.release();
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for (cv::Point& p : m_maxContour)
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p += roi.tl();
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dst(roi).copyTo(pDib(rect));
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}
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply8");
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@ -172,13 +160,14 @@ void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side)
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void CImageApplyAutoCrop::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
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{
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m_rects.clear();
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if (mats.empty()) return;
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if (!mats[0].empty()) {
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apply(mats[0], 0);
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m_rects.push_back(m_rect);
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//cv::imwrite("1.bmp", mats[0]);
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}
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if (isTwoSide && mats.size() > 1)
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{
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cv::Size dSize = m_fixedSize;
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@ -187,11 +176,66 @@ void CImageApplyAutoCrop::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
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if (!mats[1].empty()) {
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apply(mats[1], 1);
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m_rects.push_back(m_rect);
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//cv::imwrite("1.bmp", mats[0]);
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}
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if (!mats[0].empty())
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m_fixedSize = dSize;
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}
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}
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}
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cv::Scalar CImageApplyAutoCrop::getBackGroudColor(const cv::Mat& image, int total)
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{
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if (image.channels() == 3)
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{
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cv::Mat image_bgr[3];
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cv::split(image, image_bgr);
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uchar bgr[3];
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for (size_t i = 0; i < 3; i++)
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bgr[i] = getBackGroudChannelMean(image_bgr[i], total);
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return cv::Scalar(bgr[0], bgr[1], bgr[2]);
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}
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else
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return cv::Scalar::all(getBackGroudChannelMean(image, total));
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}
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uchar CImageApplyAutoCrop::getBackGroudChannelMean(const cv::Mat& gray, int total)
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{
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cv::Mat image_clone;
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cv::resize(gray, image_clone, cv::Size(), 0.25, 0.25);
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int threnshold = total / 32;
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int channels[] = { 0 };
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int nHistSize[] = { 256 };
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float range[] = { 0, 256 };
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const float* fHistRanges[] = { range };
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cv::Mat hist;
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cv::calcHist(&image_clone, 1, channels, cv::Mat(), hist, 1, nHistSize, fHistRanges, true, false);
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int hist_array[256];
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for (int i = 0; i < 256; i++)
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hist_array[i] = hist.at<float>(i, 0);
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int length = 1;
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const int length_max = 255 - m_threshold;
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while (length < length_max)
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{
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for (size_t i = m_threshold + 1; i < 256 - length; i++)
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{
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int count = 0;
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uint pixSum = 0;
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for (size_t j = 0; j < length; j++)
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{
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count += hist_array[j + i];
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pixSum += hist_array[j + i] * (i + j);
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}
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if (count >= threnshold)
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return pixSum / count;
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}
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length++;
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}
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return 255;
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}
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@ -1,3 +1,21 @@
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/*
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* ====================================================
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* 功能：自动裁剪、纠偏、除黑底
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* 作者：刘丁维
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* 生成时间：2020/4/21
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* 最近修改时间：2020/4/21 v1.0
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2020/7/22 v1.1 增加获取图像有效区域轮廓的接口maxContour（用于配合一体机的“跳过空白页”算法，PC端暂时无需使用）
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2020/10/16 v1.2 修复自动裁剪尺寸精度丢失的BUG；提高除黑底缩进精度。
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2020/10/28 v1.2.1 修复凹凸多边形填充背景的逻辑BUG。
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2020/10/28 v1.2.2 修复图像处理必定会缩小尺寸的BUG。
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2020/10/29 v1.2.3 避免无谓的纠偏（0°纠偏）
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2020/11/30 v1.3.0 增加功能，可识别文稿颜色进行填充黑底。
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* 版本号：v1.3.0
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* ====================================================
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*/
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#ifndef IMAGE_APPLY_AUTO_CROP_H
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#define IMAGE_APPLY_AUTO_CROP_H
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@ -8,7 +26,18 @@ class CImageApplyAutoCrop : public CImageApply
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public:
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CImageApplyAutoCrop();
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CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex = true, double threshold = 40, int noise = 40, int indent = 5);
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/*
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* isCrop [in]:自动幅面裁剪使能，true自动裁剪，false为固定裁剪
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* isDesaskew [in]:自动纠偏使能，true自动纠偏，false为不纠偏
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* isFillBlank [in]:黑底填充使能，true为填充，false为不填充
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* fixedSize [in]:固定幅面尺寸，当isCrop为false时生效，结果尺寸按fixedSize大小输出，单位像素
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* isConvex [in]:黑底填充时的填充方式,true为凸多边形填充，false为凹多边形填充，默认true
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* isFillColor [in]:黑底填充时采用自适应色彩填充，false为白色填充，true为自适应文稿底色填充，默认false
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* threshold [in]:二值化阈值，取值范围(0, 255)，默认40
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* noise [in]:除噪像素，能够消除noise宽度的背景竖条纹干扰，默认40
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* indent [in]:轮廓缩进，裁剪、纠偏或者黑底填充时，对探索到的纸张轮廓进行缩进indent像素，默认5
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*/
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CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex = true, double threshold = 40, int noise = 2, int indent = 5);
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virtual ~CImageApplyAutoCrop();
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@ -26,6 +55,10 @@ public:
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double threshold() { return m_threshold; }
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const cv::RotatedRect& rotatedROI() { return m_rect; }
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const std::vector<cv::RotatedRect>& rotatedROIs() { return m_rects; }
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int noise() { return m_noise; }
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int indent() { return m_indent; }
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@ -50,19 +83,25 @@ public:
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void setFixedSize(cv::Size size) { m_fixedSize = size; }
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private:
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cv::Scalar getBackGroudColor(const cv::Mat& image, int total);
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uchar getBackGroudChannelMean(const cv::Mat& gray, int total);
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private:
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bool m_isCrop;
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bool m_isDesaskew;
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bool m_isFillBlank;
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bool m_isConvexHull;
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bool m_isFillColor;
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double m_threshold;
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int m_noise;
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int m_indent;
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cv::Size m_fixedSize;
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cv::RotatedRect m_rect;
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std::vector<cv::Point> m_maxContour;
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std::vector<cv::RotatedRect> m_rects;
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};
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#endif // !IMAGE_APPLY_AUTO_CROP_H
|
||||
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||||
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||||
|
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Reference in New Issue