Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. In this research, a Crow Search Algorithm (CSA)-based metaheuristic strategy for feature extraction in HCR was developed. The data representa...
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| Format: | Conference or Workshop Item |
| Language: | English English |
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Institute of Electrical and Electronics Engineers Inc.
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/40313/1/Crow%20search%20Freeman%20Chain%20Code%20%28CS-FCC%29%20feature.pdf http://umpir.ump.edu.my/id/eprint/40313/2/Crow%20Search%20Freeman%20Chain%20Code%20%28CS-FCC%29%20feature%20extraction%20algorithm%20for%20handwritten%20character%20recognition_ABS.pdf |
| _version_ | 1825815462073597952 |
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| author | Muhammad Arif, Mohamad Zalili, Musa Amelia Ritahani, Ismail |
| author_facet | Muhammad Arif, Mohamad Zalili, Musa Amelia Ritahani, Ismail |
| author_sort | Muhammad Arif, Mohamad |
| collection | UMP |
| description | With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. In this research, a Crow Search Algorithm (CSA)-based metaheuristic strategy for feature extraction in HCR was developed. The data representation method employed was Freeman Chain Code (FCC). The fundamental issue with using FCC to represent a character is that the outcomes of the extractions depend on the starting points that changed the chain code's route length. The shortest route length and least amount of computational time for HCR were found using the metaheuristic technique via CSA, which was suggested as a solution to this issue. The suggested CS-FCC extraction algorithm's computation durations and route lengths serve as performance indicators. The algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. According to the results, the proposed CS-FCC has a route length of 1880.28 and only takes 1.10 seconds to solve the entire set of character images. |
| first_indexed | 2024-04-22T01:25:47Z |
| format | Conference or Workshop Item |
| id | UMPir40313 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-04-22T01:25:47Z |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | UMPir403132024-04-16T04:04:37Z http://umpir.ump.edu.my/id/eprint/40313/ Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition Muhammad Arif, Mohamad Zalili, Musa Amelia Ritahani, Ismail QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. In this research, a Crow Search Algorithm (CSA)-based metaheuristic strategy for feature extraction in HCR was developed. The data representation method employed was Freeman Chain Code (FCC). The fundamental issue with using FCC to represent a character is that the outcomes of the extractions depend on the starting points that changed the chain code's route length. The shortest route length and least amount of computational time for HCR were found using the metaheuristic technique via CSA, which was suggested as a solution to this issue. The suggested CS-FCC extraction algorithm's computation durations and route lengths serve as performance indicators. The algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. According to the results, the proposed CS-FCC has a route length of 1880.28 and only takes 1.10 seconds to solve the entire set of character images. Institute of Electrical and Electronics Engineers Inc. 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40313/1/Crow%20search%20Freeman%20Chain%20Code%20%28CS-FCC%29%20feature.pdf pdf en http://umpir.ump.edu.my/id/eprint/40313/2/Crow%20Search%20Freeman%20Chain%20Code%20%28CS-FCC%29%20feature%20extraction%20algorithm%20for%20handwritten%20character%20recognition_ABS.pdf Muhammad Arif, Mohamad and Zalili, Musa and Amelia Ritahani, Ismail (2023) Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition. In: 8th International Conference on Software Engineering and Computer Systems, ICSECS 2023 , 25-27 August 2023 , Penang. pp. 258-262. (192961). ISBN 979-835031093-1 (Published) https://doi.org/10.1109/ICSECS58457.2023.10256286 |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Muhammad Arif, Mohamad Zalili, Musa Amelia Ritahani, Ismail Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition |
| title | Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition |
| title_full | Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition |
| title_fullStr | Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition |
| title_full_unstemmed | Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition |
| title_short | Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition |
| title_sort | crow search freeman chain code cs fcc feature extraction algorithm for handwritten character recognition |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://umpir.ump.edu.my/id/eprint/40313/1/Crow%20search%20Freeman%20Chain%20Code%20%28CS-FCC%29%20feature.pdf http://umpir.ump.edu.my/id/eprint/40313/2/Crow%20Search%20Freeman%20Chain%20Code%20%28CS-FCC%29%20feature%20extraction%20algorithm%20for%20handwritten%20character%20recognition_ABS.pdf |
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