转载请附原文链接:http://blog.fandong.me/2017/03/09/iOS-opencv/
突如其来的来了一个App亮点
在拍摄身份证图片准备上传的时候,直接裁减掉除身份证外多余的部分! 好吧! 废话不多说! 先看效果
#第一步:获取图片 移动设备获取图片有两种方式 1.拍照2.从相册中选取如果以上你不会,那请关闭页面,去看吐槽大会(本人最近特别喜欢的综艺节目)吐槽大会直达链接
#第二步:操作图片 主要用到了Stackflow大神的一些代码
```
//寻找范围
void find_squares(cv::Mat& image, std::vector>&squares) {
// blur will enhance edge detection
cv::Mat blurred(image);
// medianBlur(image, blurred, 9);
GaussianBlur(image, blurred, cvSize(11,11), 0);//change from median blur to gaussian for more accuracy of square detection
cv::Mat gray0(blurred.size(), CV_8U), gray;
std::vector > 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 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);
}
}
}
}
}
//寻找最大范围
void find_largest_square(const std::vector >& squares, std::vector& biggest_square){
if (!squares.size()){
// no squares detected
return;
}
int max_width = 0;
int max_height = 0;
int max_square_idx = 0;
for (size_t i = 0; i < squares.size(); i++){
// Convert a set of 4 unordered Points into a meaningful cv::Rect structure.
cv::Rect rectangle = boundingRect(cv::Mat(squares[i]));
// cout << "find_largest_square: #" << i << " rectangle x:" << rectangle.x << " y:" << rectangle.y << " " << rectangle.width << "x" << rectangle.height << endl;
// Store the index position of the biggest square found
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];
}
//获取角度
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);
}
```
#第三步:获取结果图片 更多详细内容请查看GitHub:https://github.com/fandongtongxue/FDOpenCVDemo
