Zero-One Matrix on Tudung Saji Pattern via Image Processing
Pattern recognition is a method for classifying or describing the quantitative measurement of features of any object, data, or source. It involves any input that depends on the context of the study, such as biometric data, sensor data, signals, images, and so on. Prior research had been conducted on...
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Semarak Ilmu Publishing
2025
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2-s2.0-85193749971 Ramli M.; Ahmad M.A.; Mohamad M.S. Zero-One Matrix on Tudung Saji Pattern via Image Processing 2025 Journal of Advanced Research in Applied Sciences and Engineering Technology 44 2 10.37934/araset.44.2.89101 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193749971&doi=10.37934%2faraset.44.2.89101&partnerID=40&md5=4ed6eb6491dce09f2bf7ca56fd659d8b Pattern recognition is a method for classifying or describing the quantitative measurement of features of any object, data, or source. It involves any input that depends on the context of the study, such as biometric data, sensor data, signals, images, and so on. Prior research had been conducted on tudung saji, with a particular emphasis placed on ethnographic research that was related to group theory. In order to advance the study of the relationships between tudung saji and group theory, additional analysis is undertaken to examine the pattern of tudung saji within certain finite matrix rings. This analysis involves studying the zero-one matrix that is obtained through image processing. It is important to understand the process of pattern recognition to produce the output as a classification result from the feature extraction of the input. The study focuses on the stages of image preprocessing, which include scaling, grayscale conversion, and thresholding. The binarization image is classified through feature extraction using the image of tudung saji patterns. The binarization image produces a binary value. The threshold value is calculated by using the Otsu’s Method. This method evaluates the binary value by comparing the threshold value with the grayscale value. The result assists researchers in the subsequent classification of tudung saji patterns into group theory by means of analysing the finite zero-one matrix. Hence, the classification of tudung saji patterns can be achieved by utilising finite zeroone matrices, which allows for a more comprehensive analysis of these patterns from the standpoint of group theory. In light of these considerations, a mathematical analysis is conducted on the patterns of tudung saji under the field of pattern recognition. In this analysis, the image of the tudung saji pattern serves as the input for data processing, resulting in the production of a finite zero-one matrix. © 2025, Semarak Ilmu Publishing. All rights reserved. Semarak Ilmu Publishing 24621943 English Article All Open Access; Hybrid Gold Open Access |
author |
Ramli M.; Ahmad M.A.; Mohamad M.S. |
spellingShingle |
Ramli M.; Ahmad M.A.; Mohamad M.S. Zero-One Matrix on Tudung Saji Pattern via Image Processing |
author_facet |
Ramli M.; Ahmad M.A.; Mohamad M.S. |
author_sort |
Ramli M.; Ahmad M.A.; Mohamad M.S. |
title |
Zero-One Matrix on Tudung Saji Pattern via Image Processing |
title_short |
Zero-One Matrix on Tudung Saji Pattern via Image Processing |
title_full |
Zero-One Matrix on Tudung Saji Pattern via Image Processing |
title_fullStr |
Zero-One Matrix on Tudung Saji Pattern via Image Processing |
title_full_unstemmed |
Zero-One Matrix on Tudung Saji Pattern via Image Processing |
title_sort |
Zero-One Matrix on Tudung Saji Pattern via Image Processing |
publishDate |
2025 |
container_title |
Journal of Advanced Research in Applied Sciences and Engineering Technology |
container_volume |
44 |
container_issue |
2 |
doi_str_mv |
10.37934/araset.44.2.89101 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193749971&doi=10.37934%2faraset.44.2.89101&partnerID=40&md5=4ed6eb6491dce09f2bf7ca56fd659d8b |
description |
Pattern recognition is a method for classifying or describing the quantitative measurement of features of any object, data, or source. It involves any input that depends on the context of the study, such as biometric data, sensor data, signals, images, and so on. Prior research had been conducted on tudung saji, with a particular emphasis placed on ethnographic research that was related to group theory. In order to advance the study of the relationships between tudung saji and group theory, additional analysis is undertaken to examine the pattern of tudung saji within certain finite matrix rings. This analysis involves studying the zero-one matrix that is obtained through image processing. It is important to understand the process of pattern recognition to produce the output as a classification result from the feature extraction of the input. The study focuses on the stages of image preprocessing, which include scaling, grayscale conversion, and thresholding. The binarization image is classified through feature extraction using the image of tudung saji patterns. The binarization image produces a binary value. The threshold value is calculated by using the Otsu’s Method. This method evaluates the binary value by comparing the threshold value with the grayscale value. The result assists researchers in the subsequent classification of tudung saji patterns into group theory by means of analysing the finite zero-one matrix. Hence, the classification of tudung saji patterns can be achieved by utilising finite zeroone matrices, which allows for a more comprehensive analysis of these patterns from the standpoint of group theory. In light of these considerations, a mathematical analysis is conducted on the patterns of tudung saji under the field of pattern recognition. In this analysis, the image of the tudung saji pattern serves as the input for data processing, resulting in the production of a finite zero-one matrix. © 2025, Semarak Ilmu Publishing. All rights reserved. |
publisher |
Semarak Ilmu Publishing |
issn |
24621943 |
language |
English |
format |
Article |
accesstype |
All Open Access; Hybrid Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809677881043845120 |