opencv 實現對攝像頭輸入影象中檔案及證件等的實時跟蹤，四邊形檢測及提取
阿新 • • 發佈：2019-02-20
最近有個需求：拍攝證件或紙質檔案上傳時，需要自動將拍攝背景去除，只保留證件或檔案那部分的影象。
先來一張效果圖
首先使用opencv提供的CvVideoCamera類來載入視訊流
實現CvVideoCameraDelegate的方法：
- (void)processImage:(Mat &)mat；這個代理方法能實時獲取攝像頭輸入的每一幀影象
- (void)processImage:(Mat &)mat
{
Mat src_gray, filtered, edges, dilated_edges;
//獲取灰度影象
cvtColor(mat, src_gray, COLOR_BGR2GRAY);
//濾波，模糊處理，消除某些背景干擾資訊 相關自定義函式：
#pragma mark =========== 尋找最大邊框 ===========
int findLargestSquare(const vector<vector<cv::Point> >& squares, vector<cv::Point>& biggest_square)
{
if (!squares.size()) return -1;
int max_width = 0;
int max_height = 0;
int max_square_idx = 0;
for (int i = 0; i < squares.size(); i++)
{
cv::Rect rectangle = boundingRect(Mat(squares[i]));
if ((rectangle.width >= max_width) && (rectangle.height >= max_height))
{
max_width = rectangle.width;
max_height = rectangle.height;
max_square_idx = i;
}
}
biggest_square = squares[max_square_idx];
return max_square_idx;
}
/**
根據三個點計算中間那個點的夾角 pt1 pt0 pt2
*/
double getAngle(cv::Point pt1, cv::Point pt2, cv::Point pt0)
{
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
/**
點到點的距離
@param p1 點1
@param p2 點2
@return 距離
*/
double getSpacePointToPoint(cv::Point p1, cv::Point p2)
{
int a = p1.x-p2.x;
int b = p1.y-p2.y;
return sqrt(a * a + b * b);
}
/**
兩直線的交點
@param a 線段1
@param b 線段2
@return 交點
*/
cv::Point2f computeIntersect(cv::Vec4i a, cv::Vec4i b)
{
int x1 = a[0], y1 = a[1], x2 = a[2], y2 = a[3], x3 = b[0], y3 = b[1], x4 = b[2], y4 = b[3];
if (float d = ((float)(x1 - x2) * (y3 - y4)) - ((y1 - y2) * (x3 - x4)))
{
cv::Point2f pt;
pt.x = ((x1 * y2 - y1 * x2) * (x3 - x4) - (x1 - x2) * (x3 * y4 - y3 * x4)) / d;
pt.y = ((x1 * y2 - y1 * x2) * (y3 - y4) - (y1 - y2) * (x3 * y4 - y3 * x4)) / d;
return pt;
}
else
return cv::Point2f(-1, -1);
}
/**
對多個點按順時針排序
@param corners 點的集合
*/
void sortCorners(std::vector<cv::Point2f>& corners)
{
if (corners.size() == 0) return;
//先延 X軸排列
cv::Point pl = corners[0];
int index = 0;
for (int i = 1; i < corners.size(); i++)
{
cv::Point point = corners[i];
if (pl.x > point.x)
{
pl = point;
index = i;
}
}
corners[index] = corners[0];
corners[0] = pl;
cv::Point lp = corners[0];
for (int i = 1; i < corners.size(); i++)
{
for (int j = i+1; j<corners.size(); j++)
{
cv::Point point1 = corners[i];
cv::Point point2 = corners[j];
if ((point1.y-lp.y*1.0)/(point1.x-lp.x)>(point2.y-lp.y*1.0)/(point2.x-lp.x))
{
cv::Point temp = point1;
corners[i] = corners[j];
corners[j] = temp;
}
}
}
}根據四邊形的四個頂點，提取目標影象
//對頂點順時針排序
sortCorners(_corners);
//計算目標影象的尺寸
cv::Point2f p0 = _corners[0];
cv::Point2f p1 = _corners[1];
cv::Point2f p2 = _corners[2];
cv::Point2f p3 = _corners[3];
float space0 = getSpacePointToPoint(p0, p1);
float space1 = getSpacePointToPoint(p1, p2);
float space2 = getSpacePointToPoint(p2, p3);
float space3 = getSpacePointToPoint(p3, p0);
float width = space1 > space3 ? space1 : space3;
float height = space0 > space2 ? space0 : space2;
cv::Mat quad = cv::Mat::zeros(height * 3, width * 3, CV_8UC3);
std::vector<cv::Point2f> quad_pts;
quad_pts.push_back(cv::Point2f(0, quad.rows));
quad_pts.push_back(cv::Point2f(0, 0));
quad_pts.push_back(cv::Point2f(quad.cols, 0));
quad_pts.push_back(cv::Point2f(quad.cols, quad.rows));
//提取影象
cv::Mat transmtx = cv::getPerspectiveTransform(_corners , quad_pts);
cv::warpPerspective(mat, quad, transmtx, quad.size());最後可以利用 拉普拉斯運算元可以增強區域性的影象對比度，是影象更清晰
Mat imageMat;
Mat kernel = (Mat_<float>(3,3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
filter2D(quad, imageMat, quad.depth(), kernel);
//Mat --> UIImage
self.imageView.image = MatToUIImage(imageMat);好了，到這裡就基本實現了對影象中的四邊形檔案或證件的提取。
如有問題，歡迎交流！