Digit Classification of Majapahit Relic Inscription using GLCM-SVM
A higher level of image processing usually contains some kind of classification or recognition. Digit classification is an important subfield in handwritten recognition. Handwritten digits are characterized by large variations so template matching, in general, is inefficient and low in accuracy. In...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universitas Negeri Malang
2018-08-01
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| Series: | Knowledge Engineering and Data Science |
| Online Access: | http://journal2.um.ac.id/index.php/keds/article/view/3148 |
| _version_ | 1828464936117862400 |
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| author | Tri Septianto Endang Setyati Joan Santoso |
| author_facet | Tri Septianto Endang Setyati Joan Santoso |
| author_sort | Tri Septianto |
| collection | DOAJ |
| description | A higher level of image processing usually contains some kind of classification or recognition. Digit classification is an important subfield in handwritten recognition. Handwritten digits are characterized by large variations so template matching, in general, is inefficient and low in accuracy. In this paper, we propose the classification of the digit of the year of a relic inscription in the Kingdom of Majapahit using Support Vector Machine (SVM). This method is able to cope with very large feature dimensions and without reducing existing features extraction. While the method used for feature extraction using the Gray-Level Co-Occurrence Matrix (GLCM), special for texture analysis. This experiment is divided into 10 classification class, namely: class 1, 2, 3, 4, 5, 6, 7, 8, 9, and class 0. Each class is tested with 10 data so that the whole data testing are 100 data number year. The use of GLCM and SVM methods have obtained an average of classification results about 77 %. |
| first_indexed | 2024-12-11T03:23:16Z |
| format | Article |
| id | doaj.art-ab882ceb251b4db2a3eefe6b569dc181 |
| institution | Directory Open Access Journal |
| issn | 2597-4602 2597-4637 |
| language | English |
| last_indexed | 2024-12-11T03:23:16Z |
| publishDate | 2018-08-01 |
| publisher | Universitas Negeri Malang |
| record_format | Article |
| series | Knowledge Engineering and Data Science |
| spelling | doaj.art-ab882ceb251b4db2a3eefe6b569dc1812022-12-22T01:22:35ZengUniversitas Negeri MalangKnowledge Engineering and Data Science2597-46022597-46372018-08-0112465410.17977/um018v1i22018p46-542517Digit Classification of Majapahit Relic Inscription using GLCM-SVMTri Septianto0Endang Setyati1Joan Santoso2Sekolah Tinggi Teknik SurabayaSekolah Tinggi Teknik SurabayaSekolah Tinggi Teknik SurabayaA higher level of image processing usually contains some kind of classification or recognition. Digit classification is an important subfield in handwritten recognition. Handwritten digits are characterized by large variations so template matching, in general, is inefficient and low in accuracy. In this paper, we propose the classification of the digit of the year of a relic inscription in the Kingdom of Majapahit using Support Vector Machine (SVM). This method is able to cope with very large feature dimensions and without reducing existing features extraction. While the method used for feature extraction using the Gray-Level Co-Occurrence Matrix (GLCM), special for texture analysis. This experiment is divided into 10 classification class, namely: class 1, 2, 3, 4, 5, 6, 7, 8, 9, and class 0. Each class is tested with 10 data so that the whole data testing are 100 data number year. The use of GLCM and SVM methods have obtained an average of classification results about 77 %.http://journal2.um.ac.id/index.php/keds/article/view/3148 |
| spellingShingle | Tri Septianto Endang Setyati Joan Santoso Digit Classification of Majapahit Relic Inscription using GLCM-SVM Knowledge Engineering and Data Science |
| title | Digit Classification of Majapahit Relic Inscription using GLCM-SVM |
| title_full | Digit Classification of Majapahit Relic Inscription using GLCM-SVM |
| title_fullStr | Digit Classification of Majapahit Relic Inscription using GLCM-SVM |
| title_full_unstemmed | Digit Classification of Majapahit Relic Inscription using GLCM-SVM |
| title_short | Digit Classification of Majapahit Relic Inscription using GLCM-SVM |
| title_sort | digit classification of majapahit relic inscription using glcm svm |
| url | http://journal2.um.ac.id/index.php/keds/article/view/3148 |
| work_keys_str_mv | AT triseptianto digitclassificationofmajapahitrelicinscriptionusingglcmsvm AT endangsetyati digitclassificationofmajapahitrelicinscriptionusingglcmsvm AT joansantoso digitclassificationofmajapahitrelicinscriptionusingglcmsvm |