Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
In order to improve the classification accuracy in the field of handwriting character recognition (HCR), the number of derivative algorithms has improved and the interest in feature extraction has increased. In this paper, we propose a metaheuristic method for feature extraction algorithm with Whale...
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/33451/ http://umpir.ump.edu.my/id/eprint/33451/1/Whale%20Optimisation%20Freeman%20Chain%20Code%20%28WO-FCC%29%20extraction%20algorithm.pdf |
| _version_ | 1848824258058256384 |
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| author | Muhammad Arif, Mohamad Jamaludin, Sallim Kohbalan, Moorthy |
| author_facet | Muhammad Arif, Mohamad Jamaludin, Sallim Kohbalan, Moorthy |
| author_sort | Muhammad Arif, Mohamad |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | In order to improve the classification accuracy in the field of handwriting character recognition (HCR), the number of derivative algorithms has improved and the interest in feature extraction has increased. In this paper, we propose a metaheuristic method for feature extraction algorithm with Whale Optimisation Algorithm (WOA) based HCR. WOA is a swarm-based techniques that mimic the social behavior of groups of animals, which mimics the social behavior of humpback whales. Freeman chaincode (FCC) is utilised as a data representations of handwritten text images. Nevertheless, the representations of FCC depends on the length of the path and the branching of the character’s nodes. To solve this problem, we propose a metaheuristic approach through WOA to find the shortest path length and minimum computational time for handwriting recognition. Finally, the results were compared with the existing proposed Flower Pollination Algorithm (FPA) at the time of FCC extraction. The results show that WOA is a bit better at getting shorter path lengths than FPA in terms of path lengths. In terms of calculation time, WOA calculates faster calculation time by feature extraction than FPA. |
| first_indexed | 2025-11-15T03:10:10Z |
| format | Conference or Workshop Item |
| id | ump-33451 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:10:10Z |
| publishDate | 2021 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-334512022-04-07T02:43:51Z http://umpir.ump.edu.my/id/eprint/33451/ Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition Muhammad Arif, Mohamad Jamaludin, Sallim Kohbalan, Moorthy QA76 Computer software T Technology (General) In order to improve the classification accuracy in the field of handwriting character recognition (HCR), the number of derivative algorithms has improved and the interest in feature extraction has increased. In this paper, we propose a metaheuristic method for feature extraction algorithm with Whale Optimisation Algorithm (WOA) based HCR. WOA is a swarm-based techniques that mimic the social behavior of groups of animals, which mimics the social behavior of humpback whales. Freeman chaincode (FCC) is utilised as a data representations of handwritten text images. Nevertheless, the representations of FCC depends on the length of the path and the branching of the character’s nodes. To solve this problem, we propose a metaheuristic approach through WOA to find the shortest path length and minimum computational time for handwriting recognition. Finally, the results were compared with the existing proposed Flower Pollination Algorithm (FPA) at the time of FCC extraction. The results show that WOA is a bit better at getting shorter path lengths than FPA in terms of path lengths. In terms of calculation time, WOA calculates faster calculation time by feature extraction than FPA. IEEE 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33451/1/Whale%20Optimisation%20Freeman%20Chain%20Code%20%28WO-FCC%29%20extraction%20algorithm.pdf Muhammad Arif, Mohamad and Jamaludin, Sallim and Kohbalan, Moorthy (2021) Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition. In: IEEE 2021 International Conference on Software Engineering & Computer Systems and 4th International Conference on Computational Science and Information Management (ICSECS-ICOCSIM) , 24-26 August 2021 , Pekan, Pahang, Malaysia. pp. 598-602.. ISBN 978-1-6654-1407-4 (Published) https://doi.org/10.1109/ICSECS52883.2021.00115 |
| spellingShingle | QA76 Computer software T Technology (General) Muhammad Arif, Mohamad Jamaludin, Sallim Kohbalan, Moorthy Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition |
| title | Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition |
| title_full | Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition |
| title_fullStr | Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition |
| title_full_unstemmed | Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition |
| title_short | Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition |
| title_sort | whale optimisation freeman chain code (wo-fcc) extraction algorithm for handwritten character recognition |
| topic | QA76 Computer software T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/33451/ http://umpir.ump.edu.my/id/eprint/33451/ http://umpir.ump.edu.my/id/eprint/33451/1/Whale%20Optimisation%20Freeman%20Chain%20Code%20%28WO-FCC%29%20extraction%20algorithm.pdf |