IEICE TRANSACTIONS on Fundamentals
Accelerated Image Halftoning Technique Using Improved Genetic Algorithm
Summary :
This paper presents an accelerated image halftoning technique using an improved genetic algorithm with tiny populations. The algorithm is based on a new cooperative model for genetic operators in GA. Two kinds of operators are used in parallel to produce offspring: (i) SRM (Self-Reproduction with Mutation) to introduce diversity by means of Adaptive Dynamic-Block (ADB) mutation inducing the appearance of beneficial mutations. (ii) CM (Crossover and Mutation) to promote the increase of beneficial mutations in the population. SRM applies qualitative mutation only to the bits inside a mutation block and controls the required exploration-exploitation balance through its adaptive mechanism. An extinctive selection mechanism subjects SRM's and CM's offspring to compete for survival. The simulation results show that our scheme impressively reduces computer memory and processing time required to obtain high quality halftone images. For example, compared to the conventional image halftoning technique with GA, the proposed algorithm using only a 2% population size required about 15% evaluations to generate high quality images. The results make our scheme appealing for practical implementations of the image halftoning technique using GA.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.8 pp.1566-1574
- Publication Date
- 2000/08/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on Digital Signal Processing)
- Category
- Image/Visual Signal Processing
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Hernan AGUIRRE, Kiyoshi TANAKA, Tatsuo SUGIMURA, "Accelerated Image Halftoning Technique Using Improved Genetic Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 8, pp. 1566-1574, August 2000, doi: .
Abstract: This paper presents an accelerated image halftoning technique using an improved genetic algorithm with tiny populations. The algorithm is based on a new cooperative model for genetic operators in GA. Two kinds of operators are used in parallel to produce offspring: (i) SRM (Self-Reproduction with Mutation) to introduce diversity by means of Adaptive Dynamic-Block (ADB) mutation inducing the appearance of beneficial mutations. (ii) CM (Crossover and Mutation) to promote the increase of beneficial mutations in the population. SRM applies qualitative mutation only to the bits inside a mutation block and controls the required exploration-exploitation balance through its adaptive mechanism. An extinctive selection mechanism subjects SRM's and CM's offspring to compete for survival. The simulation results show that our scheme impressively reduces computer memory and processing time required to obtain high quality halftone images. For example, compared to the conventional image halftoning technique with GA, the proposed algorithm using only a 2% population size required about 15% evaluations to generate high quality images. The results make our scheme appealing for practical implementations of the image halftoning technique using GA.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_8_1566/_p
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@ARTICLE{e83-a_8_1566,
author={Hernan AGUIRRE, Kiyoshi TANAKA, Tatsuo SUGIMURA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Accelerated Image Halftoning Technique Using Improved Genetic Algorithm},
year={2000},
volume={E83-A},
number={8},
pages={1566-1574},
abstract={This paper presents an accelerated image halftoning technique using an improved genetic algorithm with tiny populations. The algorithm is based on a new cooperative model for genetic operators in GA. Two kinds of operators are used in parallel to produce offspring: (i) SRM (Self-Reproduction with Mutation) to introduce diversity by means of Adaptive Dynamic-Block (ADB) mutation inducing the appearance of beneficial mutations. (ii) CM (Crossover and Mutation) to promote the increase of beneficial mutations in the population. SRM applies qualitative mutation only to the bits inside a mutation block and controls the required exploration-exploitation balance through its adaptive mechanism. An extinctive selection mechanism subjects SRM's and CM's offspring to compete for survival. The simulation results show that our scheme impressively reduces computer memory and processing time required to obtain high quality halftone images. For example, compared to the conventional image halftoning technique with GA, the proposed algorithm using only a 2% population size required about 15% evaluations to generate high quality images. The results make our scheme appealing for practical implementations of the image halftoning technique using GA.},
keywords={},
doi={},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - Accelerated Image Halftoning Technique Using Improved Genetic Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1566
EP - 1574
AU - Hernan AGUIRRE
AU - Kiyoshi TANAKA
AU - Tatsuo SUGIMURA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2000
AB - This paper presents an accelerated image halftoning technique using an improved genetic algorithm with tiny populations. The algorithm is based on a new cooperative model for genetic operators in GA. Two kinds of operators are used in parallel to produce offspring: (i) SRM (Self-Reproduction with Mutation) to introduce diversity by means of Adaptive Dynamic-Block (ADB) mutation inducing the appearance of beneficial mutations. (ii) CM (Crossover and Mutation) to promote the increase of beneficial mutations in the population. SRM applies qualitative mutation only to the bits inside a mutation block and controls the required exploration-exploitation balance through its adaptive mechanism. An extinctive selection mechanism subjects SRM's and CM's offspring to compete for survival. The simulation results show that our scheme impressively reduces computer memory and processing time required to obtain high quality halftone images. For example, compared to the conventional image halftoning technique with GA, the proposed algorithm using only a 2% population size required about 15% evaluations to generate high quality images. The results make our scheme appealing for practical implementations of the image halftoning technique using GA.
ER -
English
