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222
Learning OpenCV Lecture 2 (Using the Strategy pattern in algorithm design) - 爱码网
ColorDetector.h:
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
class ColorDetector
{
public:
// empty constructor
ColorDetector() : minDist(100) {
// default parameter initialization here
target[0] = target[1] = target[2] = 0;
}
// Sets the color distance threshold
// Threshold must be positive
// othrewise distance threshold is set to 0.
void setColorDistanceThreshold(int distance) {
if (distance < 0) {
distance = 0;
}
minDist = distance;
}
// Gets the color distance threshold
int getColorDistanceThreshold() const {
return minDist;
}
// Sets the color to be detected
void setTargetColor(unsigned char red,
unsigned char green,
unsigned char blue) {
// BGR order
target[2] = red;
target[1] = green;
target[0] = blue;
}
// Sets the color to be detected
void setTargetColor(cv::Vec3b color) {
target = color;
}
// Gets the color to be detected
cv::Vec3b getTargetColor() const {
return target;
}
cv::Mat process(const cv::Mat &image);
int getDistance(const cv::Vec3b& color) const;
private:
// minimum acceptable distance
int minDist;
// target color
cv::Vec3b target;
// image containing resulting binary map
cv::Mat result;
};
ColorDetector.cpp:
#include "ColorDetector.h"
cv::Mat ColorDetector::process(const cv::Mat &image) {
// re-allocate binary map if necessary
// same size as input image, but 1-chaanel
result.create(image.rows, image.cols, CV_8U);
// get the iterators
cv::Mat_<cv::Vec3b>::const_iterator it = image.begin<cv::Vec3b>();
cv::Mat_<cv::Vec3b>::const_iterator itend = image.end<cv::Vec3b>();
cv::Mat_<uchar>::iterator itout = result.begin<uchar>();
// for each pixel
for ( ; it!= itend; ++it, ++itout) {
// process each pixel ---------------------
// compute distance from target color
if (getDistance(*it) < minDist) {
*itout = 255;
} else {
*itout = 0;
}
// end of pixel processing ----------------
}
return result;
}
int ColorDetector::getDistance(const cv::Vec3b& color) const {
return abs(color[0] - target[0]) +
abs(color[1] - target[1]) +
abs(color[2] - target[2]);
// Other methods to compute distance
// return static_cast<int>(
// cv::norm<int, 3>(cv::Vec3b(color[0] - target[0],
// color[1] - target[1],
// color[2] - target[2])));
}
main.cpp
#include "ColorDetector.h"
int main()
{
// 1. Create image processor boject
ColorDetector cdetect;
// 2. Read input image
cv::Mat image = cv::imread( "test.jpg");
if (!image.data) {
return 0;
}
// 3. Set input parameters
cdetect.setTargetColor(130, 190, 230); // here blue sky
cv::namedWindow( "result");
// 4. Process the image and display the result
cv::imshow( "result", cdetect.process(image));
cv::waitKey();
return 0;
}
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