Vision-based chicken meat freshness recognition system using RGB color moment features and support vector machine

Sutarman, - and Avianto, Donny and Wibowo, Adityo Permana (2023) Vision-based chicken meat freshness recognition system using RGB color moment features and support vector machine. Science in Information Technology Letters, 4 (2). pp. 65-74. ISSN 2722-4139

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Abstract

Chicken meat is a highly sought-after food product among various segments of the general population, known for its high nutritional value and easy accessibility. Presently, meat identification is primarily conducted manually, relying on visual inspection or tactile assessment of the meat's color and texture. However, this approach presents several limitations, particularly when consumers lack the discernment to differentiate the quality of chicken meat freshness. This research aims to identify the freshness level of chicken meat using the Support Vector Machine method, employing the extraction of RGB color moment features to determine the freshness of the meat. The feature extraction process involves calculating the percentage of intensity values for R (Red), G (Green), and B (Blue) in each chicken meat image. Based on the image processing results, the percentage of intensity values, particularly in the R and B parameters, can be used as determining factors. The study involves software testing using fresh and non-fresh chicken meat. The developed system can identify the freshness level of fresh chicken meat with an accuracy rate of 71.6% using the linear kernel SVM and 60.5% using the RBF kernel SVM. This research represents a significant step toward the automation of chicken meat freshness assessment, potentially reducing food waste and enhancing food safety in the food industry. Further research and development could improve the system's accuracy and expand its applications in various food quality control settings.

Item Type:	Article
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Pascasarjana > Magister Teknologi Informasi
Depositing User:	Ph.D Sutarman UTY
Date Deposited:	15 Jan 2024 04:51
Last Modified:	15 Jan 2024 07:46
URI:	http://eprints.uty.ac.id/id/eprint/14791

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