Algorithm Symmetric 2-DLDA for Recognizing Handwritten Capital Letters
DOI:
https://doi.org/10.30812/matrik.v21i2.1254Keywords:
Capital Letter, DLDA, Recognition usingAbstract
Statistical pattern recognition is the process of using statistical techniques to obtain information and make informed decisions based on data measurements. It is possible to solve the doubt inherent in the objective function of the 2-Dimension Linear Discriminant Analysis by employing the symmetrical 2-Dimension Linear Discriminant Analysis approach. Symmetrical 2-dimensional linear discriminant analysis has found widespread use as a method of introducing handwritten capital letters. Symmetric 2-DLDA, according to Symmetric 2-DLDA, produces better and more accurate results than Symmetric 2-DLDA. So far, pattern recognition has been based solely on computer knowledge, with no connection to statistical measurements, such as data variation and Euclidean distance, particularly in symmetrical images. As a result, the aim of this research is to create algorithms for recognizing capital letter patterns in a wide range of handwriting. The ADL2-D symmetric method is used in this study as the development of the ADL2-D method. The research results in an algorithm that considers the left and right sides of the image matrix, as opposed to ADL2-D, which does not consider the left and right sides of the image matrix. In pattern recognition, the results with symmetric ADL2-D are more accurate
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References
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[3] I. M. Pegi, K. Amerta, and I. G. A. Wibawa, “Alphabet Writing Game Application using Template Matching Cross-correlation,†vol. 8, no. 4, pp. 393–399, 2020.
[4] A. Challa, “Automatic Handwritten Digit Recognition On Document Images Using Machine Learning Methods,†Blekinge Inst. Technol., no. January, 2019.
[5] M. M. Saufi, M. A. Zamanhuri, N. Mohammad, and Z. Ibrahim, “Deep learning for roman handwritten character recognition,†Indones. J. Electr. Eng. Comput. Sci., vol. 12, no. 2, pp. 455–460, 2018, doi: 10.11591/ijeecs.v12.i2.pp455-460.
[6] I. Raya et al., “Kinetic, isotherm, and thermodynamic studies on Cr(VI) adsorption using cellulose acetate/graphene oxide composite nanofibers,†Appl. Phys. A Mater. Sci. Process., vol. 128, no. 2, 2022, doi: 10.1007/s00339-022-05307-4.
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[8] M. Tokovarov, M. Kaczorowska, and M. Milosz, “Development of Extensive Polish Handwritten Characters Database for Text Recognition Research,†Adv. Sci. Technol. Res. J., vol. 14, no. 3, pp. 30–38, 2020, doi: 10.12913/22998624/122567.
[9] M. J. Al-Shamdeen, A. N. Younis, and H. A. Younis, “Metaheuristic Algorithm for Capital Letters Images Recognition,†Int. J. Math. Comput. Sci., vol. 16, no. 2, pp. 577–588, 2020.
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[11] M. Domino et al., “Selection of Image Texture Analysis and Color Model in the Advanced Image Processing of Thermal Images of Horses following Exercise,†Animals, vol. 12, no. 4, 2022, doi: 10.3390/ani12040444.
[12] and L. Li, J.,Chen, Z., “Low-resolution Face Recognation of Multi-scale Blocking CS-LBP and Weighted PCA,†Int. J. Pattern Recognit. Artif. Intell., vol. 30, no. 10, 2018.
[13] Y. Zhao, D., Chen, Z., Liu, C., Peng, “Two-dimensional Linear Discriminant Analysis for Low-Resolution Face Recognition,†IEEE, 2018.
[14] H. Luo, D., Ding, C., and Huang, “Symmetric Two Dimensional Linear,†in University of Texas at Arlington Press, 2019.
[15] I. H. Gerhard Wilhelm Weber, Burcu Gurbuz, Herman Mawengkang, “Rumour Propogation : an operational research approach by computional and information theory,†CEJOR, vol. 4, no. 4, 2022.
[16] S. E. Husain, Muhammad Zarlis, Herman Mawengkang, “Causal Loop Diagram (CLD) Model In Planning A Sustainable Smart Sharia Tourism,†J. Phys.Conf. Ser, vol. 1641, no. 012099, 2020.
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Published
2022-03-31
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Articles
How to Cite
[1]
I. Husein and R. Widyasari, “Algorithm Symmetric 2-DLDA for Recognizing Handwritten Capital Letters”, MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 21, no. 2, pp. 389–402, Mar. 2022, doi: 10.30812/matrik.v21i2.1254.
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