#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; }
Learning OpenCV Lecture 2 (Using the Strategy pattern in algorithm design),布布扣,bubuko.com
Learning OpenCV Lecture 2 (Using the Strategy pattern in algorithm design)
原文地址：http://www.cnblogs.com/starlitnext/p/3861331.html
