Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination using the handwritten numeral characters
Handwriting is unique in which no two individuals can write the same way regardless they are identical or fraternal twins. Everyone has their own unique handwriting style or their natural handwriting variations which are influenced by a variety of factors which include their ethnic background or cul...
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| Format: | Thesis |
| Language: | English |
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2024
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| Online Access: | http://eprints.usm.my/61982/ http://eprints.usm.my/61982/1/WAN%20NURUL%20SYAFAWANI%20BINTI%20WAN%20MOHD%20TAUFEK-FINAL%20THESIS%20P-SKD002018%28R%29-E.pdf |
| _version_ | 1848884857669681152 |
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| author | Taufek, Wan Nurul Syafawani Wan Mohd |
| author_facet | Taufek, Wan Nurul Syafawani Wan Mohd |
| author_sort | Taufek, Wan Nurul Syafawani Wan Mohd |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Handwriting is unique in which no two individuals can write the same way regardless they are identical or fraternal twins. Everyone has their own unique handwriting style or their natural handwriting variations which are influenced by a variety of factors which include their ethnic background or cultural background. Nonetheless, discriminating individuals’ ethnicity based on their handwriting characters, let alone the handwritten numeral characters, is limited even though the handwritten numeral characters analysis can be crucial in assisting forensic document examiner (FDE) in solving crimes related to dubious documents. The general objective of this study was to investigate whether it is possible to discriminate authors based on their ethnic background by utilising their handwritten numeral characters using novel Geometric Morphometric (GMM) technique. The handwritten numeral characters of 0 until 9 were collected from 390 participants from three different ethnic backgrounds in Malaysia which had been digitised and landmarked using TpsUtil1.78 and TpsDig2 software respectively, prior to GMM assessment using MorphoJ and Minitab software. From the results, two-dimensional (2D) and three-dimensional (3D) of Principal Component Analysis (PCA) scatterplots demonstrated identifiable cluster patterns between Malay, Chinese and Indian authors. Besides, there were significant differences in the handwritten numerals 2 through 9 between Malay, Chinese and Indian authors when the datasets tested using Procrustes Analysis of Variance (ANOVA) (p<0.0001) and Discriminant Function Analysis (DFA) (p<0.0001), which that these handwritten numeral characters have potential to be used to discriminate authors based on their ethnicities. |
| first_indexed | 2025-11-15T19:13:22Z |
| format | Thesis |
| id | usm-61982 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:13:22Z |
| publishDate | 2024 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-619822025-05-19T07:22:04Z http://eprints.usm.my/61982/ Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination using the handwritten numeral characters Taufek, Wan Nurul Syafawani Wan Mohd RA1001 Forensic Medicine. Medical jurisprudence. Legal medicine RA440-440.87 Study and teaching. Research Handwriting is unique in which no two individuals can write the same way regardless they are identical or fraternal twins. Everyone has their own unique handwriting style or their natural handwriting variations which are influenced by a variety of factors which include their ethnic background or cultural background. Nonetheless, discriminating individuals’ ethnicity based on their handwriting characters, let alone the handwritten numeral characters, is limited even though the handwritten numeral characters analysis can be crucial in assisting forensic document examiner (FDE) in solving crimes related to dubious documents. The general objective of this study was to investigate whether it is possible to discriminate authors based on their ethnic background by utilising their handwritten numeral characters using novel Geometric Morphometric (GMM) technique. The handwritten numeral characters of 0 until 9 were collected from 390 participants from three different ethnic backgrounds in Malaysia which had been digitised and landmarked using TpsUtil1.78 and TpsDig2 software respectively, prior to GMM assessment using MorphoJ and Minitab software. From the results, two-dimensional (2D) and three-dimensional (3D) of Principal Component Analysis (PCA) scatterplots demonstrated identifiable cluster patterns between Malay, Chinese and Indian authors. Besides, there were significant differences in the handwritten numerals 2 through 9 between Malay, Chinese and Indian authors when the datasets tested using Procrustes Analysis of Variance (ANOVA) (p<0.0001) and Discriminant Function Analysis (DFA) (p<0.0001), which that these handwritten numeral characters have potential to be used to discriminate authors based on their ethnicities. 2024-03 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/61982/1/WAN%20NURUL%20SYAFAWANI%20BINTI%20WAN%20MOHD%20TAUFEK-FINAL%20THESIS%20P-SKD002018%28R%29-E.pdf Taufek, Wan Nurul Syafawani Wan Mohd (2024) Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination using the handwritten numeral characters. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | RA1001 Forensic Medicine. Medical jurisprudence. Legal medicine RA440-440.87 Study and teaching. Research Taufek, Wan Nurul Syafawani Wan Mohd Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination using the handwritten numeral characters |
| title | Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination
using the handwritten numeral characters |
| title_full | Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination
using the handwritten numeral characters |
| title_fullStr | Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination
using the handwritten numeral characters |
| title_full_unstemmed | Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination
using the handwritten numeral characters |
| title_short | Application of geometric morphometric (GMM) approach for author’s ethnicity discrimination
using the handwritten numeral characters |
| title_sort | application of geometric morphometric (gmm) approach for author’s ethnicity discrimination
using the handwritten numeral characters |
| topic | RA1001 Forensic Medicine. Medical jurisprudence. Legal medicine RA440-440.87 Study and teaching. Research |
| url | http://eprints.usm.my/61982/ http://eprints.usm.my/61982/1/WAN%20NURUL%20SYAFAWANI%20BINTI%20WAN%20MOHD%20TAUFEK-FINAL%20THESIS%20P-SKD002018%28R%29-E.pdf |