使用OpenCV Swift

时间:2018-08-17 09:12:48

标签: objective-c opencv edge-detection image-rotation

我正在iOS项目中使用OpenCV进行文档边缘检测,并成功检测到文档边缘。

现在,我想旋转图像以及检测到的矩形。我已经提到了 Github project来检测边缘。 为此,我首先旋转图像,并尝试通过再次找到图像的最大矩形来重新检测边缘。不幸的是,它没有给我确切的矩形。

我是否可以建议我一些方法来检测旋转文档的边缘,还是应该将检测到的矩形与图像一起旋转?

Before Rotation Image

After Rotation Image

+(NSMutableArray *) getLargestSquarePoints: (UIImage *) image : (CGSize) size {

Mat imageMat;

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, cols,  rows,  8,  cvMat.step[0], colorSpace,  kCGImageAlphaNoneSkipLast | kCGBitmapByteOrderDefault); 

CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), image.CGImage);
CGContextRelease(contextRef);

imageMat = cvMat;

cv::resize(imageMat, imageMat, cvSize(size.width, size.height));

//    UIImageToMat(image, imageMat);


std::vector<std::vector<cv::Point> >rectangle;
std::vector<cv::Point> largestRectangle;

getRectangles(imageMat, rectangle);
getlargestRectangle(rectangle, largestRectangle);

if (largestRectangle.size() == 4)
{

    //        Thanks to: https://stackoverflow.com/questions/20395547/sorting-an-array-of-x-and-y-vertice-points-ios-objective-c/20399468#20399468

    NSArray *points = [NSArray array];
    points = @[
               [NSValue valueWithCGPoint:(CGPoint){(CGFloat)largestRectangle[0].x, (CGFloat)largestRectangle[0].y}],
               [NSValue valueWithCGPoint:(CGPoint){(CGFloat)largestRectangle[1].x, (CGFloat)largestRectangle[1].y}],
               [NSValue valueWithCGPoint:(CGPoint){(CGFloat)largestRectangle[2].x, (CGFloat)largestRectangle[2].y}],
               [NSValue valueWithCGPoint:(CGPoint){(CGFloat)largestRectangle[3].x, (CGFloat)largestRectangle[3].y}]                            ];

    CGPoint min = [points[0] CGPointValue];
    CGPoint max = min;
    for (NSValue *value in points) {
        CGPoint point = [value CGPointValue];
        min.x = fminf(point.x, min.x);
        min.y = fminf(point.y, min.y);
        max.x = fmaxf(point.x, max.x);
        max.y = fmaxf(point.y, max.y);
    }

    CGPoint center = {
        0.5f * (min.x + max.x),
        0.5f * (min.y + max.y),
    };

    NSLog(@"center: %@", NSStringFromCGPoint(center));

    NSNumber *(^angleFromPoint)(id) = ^(NSValue *value){
        CGPoint point = [value CGPointValue];
        CGFloat theta = atan2f(point.y - center.y, point.x - center.x);
        CGFloat angle = fmodf(M_PI - M_PI_4 + theta, 2 * M_PI);
        return @(angle);
    };

    NSArray *sortedPoints = [points sortedArrayUsingComparator:^NSComparisonResult(id a, id b) {
        return [angleFromPoint(a) compare:angleFromPoint(b)];
    }];

    NSLog(@"sorted points: %@", sortedPoints);

    NSMutableArray *squarePoints = [[NSMutableArray alloc] init];
    [squarePoints addObject: [sortedPoints objectAtIndex:0]];
    [squarePoints addObject: [sortedPoints objectAtIndex:1]];
    [squarePoints addObject: [sortedPoints objectAtIndex:2]];
    [squarePoints addObject: [sortedPoints objectAtIndex:3]];
    imageMat.release();

    return squarePoints;


}
else{
    imageMat.release();
    return nil;
}

 }

 void getRectangles(cv::Mat& image, std::vector<std::vector<cv::Point>>&rectangles) {

// blur will enhance edge detection

cv::Mat blurred(image);
GaussianBlur(image, blurred, cvSize(11,11), 0);

cv::Mat gray0(blurred.size(), CV_8U), gray;
std::vector<std::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(&blurred, 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); //
            //                Canny(gray0, gray, 0, 50, 5);

            // 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
        std::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)
                    rectangles.push_back(approx);
            }
        }
    }
}
}

void getlargestRectangle(const std::vector<std::vector<cv::Point> >&rectangles, std::vector<cv::Point>& largestRectangle)
{
if (!rectangles.size())
{
    return;
}

double maxArea = 0;
int index = 0;

for (size_t i = 0; i < rectangles.size(); i++)
{
    cv::Rect rectangle = boundingRect(cv::Mat(rectangles[i]));
    double area = rectangle.width * rectangle.height;

    if (maxArea < area)
    {
        maxArea = area;
        index = i;
    }
}

largestRectangle = rectangles[index];
}


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);
}


+(UIImage *) getTransformedImage: (CGFloat) newWidth : (CGFloat) newHeight : (UIImage *) origImage : (CGPoint [4]) corners : (CGSize) size {

cv::Mat imageMat;


CGColorSpaceRef colorSpace = CGImageGetColorSpace(origImage.CGImage);
CGFloat cols = size.width;
CGFloat rows = 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), origImage.CGImage);
CGContextRelease(contextRef);

imageMat = cvMat;

cv::Mat newImageMat = cv::Mat( cvSize(newWidth,newHeight), CV_8UC4);

cv::Point2f src[4], dst[4];
src[0].x = corners[0].x;
src[0].y = corners[0].y;
src[1].x = corners[1].x;
src[1].y = corners[1].y;
src[2].x = corners[2].x;
src[2].y = corners[2].y;
src[3].x = corners[3].x;
src[3].y = corners[3].y;

dst[0].x = 0;
dst[0].y = -10;
dst[1].x = newWidth - 1;
dst[1].y = -10;
dst[2].x = newWidth - 1;
dst[2].y = newHeight + 1;
dst[3].x = 0;
dst[3].y = newHeight + 1;

dst[0].x = 0;
dst[0].y = 0;
dst[1].x = newWidth - 1;
dst[1].y = 0;
dst[2].x = newWidth - 1;
dst[2].y = newHeight - 1;
dst[3].x = 0;
dst[3].y = newHeight - 1;

cv::warpPerspective(imageMat, newImageMat, cv::getPerspectiveTransform(src, dst), cvSize(newWidth, newHeight));

//Transform to UIImage

NSData *data = [NSData dataWithBytes:newImageMat.data length:newImageMat.elemSize() * newImageMat.total()];

CGColorSpaceRef colorSpace2;

if (newImageMat.elemSize() == 1) {
    colorSpace2 = CGColorSpaceCreateDeviceGray();
} else {
    colorSpace2 = CGColorSpaceCreateDeviceGray();
//        colorSpace2 = CGColorSpaceCreateDeviceRGB();
}

CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);
CGFloat width = newImageMat.cols;
CGFloat height = newImageMat.rows;

CGImageRef imageRef = CGImageCreate(width, height, 8, 8 * newImageMat.elemSize(),
                                    newImageMat.step[0],
                                    colorSpace2,
                                    kCGImageAlphaNone | kCGBitmapByteOrderDefault, provider,
                                    NULL, false, kCGRenderingIntentDefault);

UIImage *image = [[UIImage alloc] initWithCGImage:imageRef];
CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace2);

return image;
}

1 个答案:

答案 0 :(得分:0)

如果使用cv2.minAreaRect,它将为轮廓和角度提供最佳的封闭矩形,因此可以向后旋转。