I had developed a system for fruit grading whose steps are segmentation, feature extraction, classification. the dimension of image n*n Number of images m then segmented image has complexity O(m.n^2) IF (n.k is a segmented part) features are extracted then complexity after feature extraction is O(m.n.k) if p is the number of features extracted then complexity after classification is O(m.p) Total Complexity=o(m(n^2+n.k+p))

I want to ask for different segmentation technique used, different number of features, different classifier used what are the changes in total complexity