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The Heuristic Extraction Algorithms for Freeman Chain Code of Handwritten Character
Dewi Nasien, Habibollah Haron, Siti Sophiayati Yuhaniz
Pages - 1 - 20     |    Revised - 31-01-2011     |    Published - 08-02-2011
Volume - 1   Issue - 1    |    Publication Date - January / February 2011  Table of Contents
Response Surface Methodology, Particle Swarm Optimization, Rhythmic Movements, Biped Robot, Central Pattern Generator, Van Der Pol Oscillators
Handwriting character recognition (HCR) is the ability of a computer to receive and interpret handwritten input. In HCR, there are many representation schemes and one of them is Freeman chain code (FCC). Chain code is a sequence of code direction of a characters and connection to a starting point which is often used in image processing. The main problem in representing character using FCC that it is depends on the starting points. Unfortunately, the study about FCC extraction using one continuous route and to minimizing the length of chain code to FCC from a thinned binary image (TBI) have not been widely explored. To solve this problem, heuristic algorithms are proposed to extract the FCC that is correctly representing the characters. This paper proposes two heuristics algorithm that are based on randomized and enumeration-based algorithms to solve the problems. As problem solving techniques, the randomized algorithm makes the random choices while enumeration-based algorithm enumerates all possible candidates for solution. The performance measures of the algorithms are the route length and computation time. The experiment on the algorithms are performed based on the chain code representation derived from established previous works of Center of Excellence for Document Analysis and Recognition (CEDAR) dataset which consists of 126 upper-case letter characters. The experimental result shows that route length of both algorithms are similar but the computation time of enumeration-based algorithm is higher than randomized algorithm. This is because enumeration-based algorithm considers all branches in route walk.
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Miss Dewi Nasien
- Malaysia
Associate Professor Habibollah Haron
- Malaysia
Dr. Siti Sophiayati Yuhaniz
- Malaysia