halftoning technique using genetic algorithm naoki kobayashi and hideo saito 1994 ieee
Post on 21-Dec-2015
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Halftoning Technique using Genetic Algorithm
There are two proposed methods for halftoning techniques using GA.
Method I-Initial Population
The initial population of n strings such as the sample is produced randomly and independently of the gray-tone block.
Method I-fitness value
bg(i,j) is a convoluted b(i,j) by the gaussian filter. gs(I,j) is the convoluted g(I,j) by the smoothing filter.
blockji
gm jibjigs
E),(
|),(),(|1
blockji
sc jibjigM
jigs
E),(
|),(),(2
),(|1
ccmmt EwEwE
tf EEF
Method I-Reproduction
The population size is n and the fitness value of the ith string is F(i), a selection’s probability P(i) of ith string
n
j
jF
iFiP
1
)(
)()(
Method I-Mutation
The string is selected randomly and one pixel in the string is inverted. The black changes to the white or the white changes to the black.
Method II-Crossover
The number of black pixels between tow strings are changed when the pixels in the local region are exchanged, some pixels are randomly selected and then exchanged between two strings for making the number of black pixels even.
Method II-Mutation
The string is selected randomly, two pixels in the string is selected randomly and the two pixels are exchanged.