我正在研究一个在大背景图像中有一个矩形图像的实现。我正在尝试以编程方式从大图像中检索矩形图像并从该特定矩形图像中检索文本信息。我正在尝试使用 Open-CV 第三方框架，但无法从大背景图像中检索矩形图像。有人可以指导我，我怎么能做到这一点？
更新：
我找到了使用 OpenCV 找出正方形的链接。我可以修改它以查找矩形形状吗？有人可以指导我吗？
最新更新：
我终于得到了代码，下面是它。
- (cv::Mat)cvMatWithImage:(UIImage *)image
{
CGColorSpaceRef colorSpace = CGImageGetColorSpace(image.CGImage);
CGFloat cols = image.size.width;
CGFloat rows = image.size.height;
cv::Mat cvMat(rows, cols, CV_8UC4); // 8 bits per component, 4 channels
CGContextRef contextRef = CGBitmapContextCreate(cvMat.data, // Pointer to backing data
cols, // Width of bitmap
rows, // Height of bitmap
8, // Bits per component
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNoneSkipLast |
kCGBitmapByteOrderDefault); // Bitmap info flags
CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), image.CGImage);
CGContextRelease(contextRef);
return cvMat;
}
-(UIImage *)UIImageFromCVMat:(cv::Mat)cvMat
{
NSData *data = [NSData dataWithBytes:cvMat.data length:cvMat.elemSize()*cvMat.total()];
CGColorSpaceRef colorSpace;
if ( cvMat.elemSize() == 1 ) {
colorSpace = CGColorSpaceCreateDeviceGray();
}
else {
colorSpace = CGColorSpaceCreateDeviceRGB();
}
//CFDataRef data;
CGDataProviderRef provider = CGDataProviderCreateWithCFData( (CFDataRef) data ); // It SHOULD BE (__bridge CFDataRef)data
CGImageRef imageRef = CGImageCreate( cvMat.cols, cvMat.rows, 8, 8 * cvMat.elemSize(), cvMat.step[0], colorSpace, kCGImageAlphaNone|kCGBitmapByteOrderDefault, provider, NULL, false, kCGRenderingIntentDefault );
UIImage *finalImage = [UIImage imageWithCGImage:imageRef];
CGImageRelease( imageRef );
CGDataProviderRelease( provider );
CGColorSpaceRelease( colorSpace );
return finalImage;
}
-(void)forOpenCV
{
imageView = [UIImage imageNamed:@"myimage.jpg"];
if( imageView != nil )
{
cv::Mat tempMat = [imageView CVMat];
cv::Mat greyMat = [self cvMatWithImage:imageView];
cv::vector<cv::vector<cv::Point> > squares;
cv::Mat img= [self debugSquares: squares: greyMat];
imageView = [self UIImageFromCVMat: img];
self.imageView.image = imageView;
}
}
double angle( 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);
}
- (cv::Mat) debugSquares: (std::vector<std::vector<cv::Point> >) squares : (cv::Mat &)image
{
NSLog(@"%lu",squares.size());
// blur will enhance edge detection
//cv::Mat blurred(image);
cv::Mat blurred = image.clone();
medianBlur(image, blurred, 9);
cv::Mat gray0(image.size(), CV_8U), gray;
cv::vector<cv::vector<cv::Point> > contours;
// find squares in every color plane of the image
for (int c = 0; c < 3; c++)
{
int ch[] = {c, 0};
mixChannels(&image, 1, &gray0, 1, ch, 1);
// try several threshold levels
const int threshold_level = 2;
for (int l = 0; l < threshold_level; l++)
{
// Use Canny instead of zero threshold level!
// Canny helps to catch squares with gradient shading
if (l == 0)
{
Canny(gray0, gray, 10, 20, 3); //
// Dilate helps to remove potential holes between edge segments
dilate(gray, gray, cv::Mat(), cv::Point(-1,-1));
}
else
{
gray = gray0 >= (l+1) * 255 / threshold_level;
}
// Find contours and store them in a list
findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
// Test contours
cv::vector<cv::Point> approx;
for (size_t i = 0; i < contours.size(); i++)
{
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(cv::Mat(contours[i]), approx, arcLength(cv::Mat(contours[i]), true)*0.02, true);
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if (approx.size() == 4 &&
fabs(contourArea(cv::Mat(approx))) > 1000 &&
isContourConvex(cv::Mat(approx)))
{
double maxCosine = 0;
for (int j = 2; j < 5; j++)
{
double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
maxCosine = MAX(maxCosine, cosine);
}
if (maxCosine < 0.3)
squares.push_back(approx);
}
}
}
}
NSLog(@"squares.size(): %lu",squares.size());
for( size_t i = 0; i < squares.size(); i++ )
{
cv::Rect rectangle = boundingRect(cv::Mat(squares[i]));
NSLog(@"rectangle.x: %d", rectangle.x);
NSLog(@"rectangle.y: %d", rectangle.y);
if(i==squares.size()-1)////Detecting Rectangle here
{
const cv::Point* p = &squares[i][0];
int n = (int)squares[i].size();
NSLog(@"%d",n);
line(image, cv::Point(507,418), cv::Point(507+1776,418+1372), cv::Scalar(255,0,0),2,8);
polylines(image, &p, &n, 1, true, cv::Scalar(255,255,0), 5, CV_AA);
int fx1=rectangle.x;
NSLog(@"X: %d", fx1);
int fy1=rectangle.y;
NSLog(@"Y: %d", fy1);
int fx2=rectangle.x+rectangle.width;
NSLog(@"Width: %d", fx2);
int fy2=rectangle.y+rectangle.height;
NSLog(@"Height: %d", fy2);
line(image, cv::Point(fx1,fy1), cv::Point(fx2,fy2), cv::Scalar(0,0,255),2,8);
}
}
return image;
}
谢谢你。