Open AccessThe Pattern Recognition System Using the Fractal Dimension of Chaos Theory
Author(s) -
Young-Woo Shon
Publication year - 2015
Publication title -
international journal of fuzzy logic and intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.296
H-Index - 9
eISSN - 2093-744X
pISSN - 1598-2645
DOI - 10.5391/ijfis.2015.15.2.121
Subject(s) - character (mathematics) , fractal dimension , box counting , dimension (graph theory) , chaos (operating system) , fractal , pattern recognition (psychology) , artificial intelligence , mathematics , effective dimension , chaos theory , correlation dimension , measure (data warehouse) , hénon map , fractal analysis , character recognition , image (mathematics) , computer science , hausdorff dimension , data mining , geometry , pure mathematics , mathematical analysis , chaotic , computer security
In this paper, we propose a method that extracts features from character patterns using the fractal dimension of chaos theory. The input character pattern image is converted into timeseries data. Then, using the modified Henon system suggested in this paper, it determines the last features of the character pattern image after calculating the box-counting dimension, natural measure, information bit, and information (fractal) dimension. Finally, character pattern recognition is performed by statistically finding each information bit that shows the minimum difference compared with a normalized character pattern database.
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