Processing Color Images, Brightness and Color Conversion

Measure of compactness for analyse dataset

“…The use of ( 10) is based on the assumption that the probability of selecting informative feature sets with a higher compactness in ( 8) is close to zero for λ other than (10). In the first (in the order of presentation) criteria, the results of covering sample objects with hyperspheres are taken into account, taking into account the removal of noise objects, in the second, compactness estimates are used according to (7) based on the property of connectivity over objects of class shells.…”

“…where 𝑋(𝑘 + 1) = 𝑋(𝑘) ∪ {𝑥 𝑑 }, 𝑇 ⊂ 𝐸 0 . Let P denote the subset of feature indices from X (n); 𝐷 𝑗 (P) is the set of noise objects of class Kj according to (5) on the set {𝑥 𝑎 } 𝑎∈𝑃 at the value λ, calculated according to (10).…”

“…Groups of first class: {0,1,10,11,19,49,3,24,31,35,45,47,15,21,16,18,20,29,37,6,7,17,23,28,46,2,4,32,38,39,4 0,34,5,8,25,26,30,33,43,9,12,27,44,22,42,41,36}, {13}, {14}, {48} -number of groups=4 Groups of second class: {50,52,83,60,65,70,72,73,93,96,97,55,78,79,94,54,62,63,76,92,66,81,69,59,90,95,51,53 ,58,88,67,89,98,57,74,64,75,77,87,91,68,56,82,85,86,71}, {61}, {80}, {84}, {99} -number of groups=5…”