Using the Strategy pattern in algorithm design

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>

class ColorDetector {
private:
// minimum acceptable distance
int minDist;
// target color
cv::Vec3b target;
// image containing resulting binary map
cv::Mat result;

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,
// otherwise distance threshold is set to 0.
void setColorDistanceThreshold(int distance) {
if (distance<0)
distance=0;
minDist= distance;
}
// Get 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;
}

int getDistance(const cv::Vec3b& color) const {
return abs(color[0]-target[0])+
abs(color[1]-target[1])+
abs(color[2]-target[2]);
}

cv::Mat ColorDetector::process(const cv::Mat &image) {
// re-allocate binary map if necessary
// same size as input image, but 1-channel
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 processiong -----------------
}
return result;
}
};

int main()
{
// 1. Create image processor object
ColorDetector cdetect;
// 2. Read input image
cv::Mat image=cv::imread("G:\\opencv\\images\\boldt.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;
}