ILLUMINATING IDENTIFICATION: ENHANCING OPTICAL RECOGNITION OF PLASTIC BOTTLES THROUGH ADVANCED LIGHTING SYSTEMS
Keywords:
Abstract
This study explores the advancement of optical recognition for plastic bottles through the implementation of sophisticated lighting systems. The research focuses on enhancing the accuracy and efficiency of identification processes, critical for recycling and waste management. Through a systematic examination of various lighting conditions, the study aims to optimize optical recognition algorithms for improved performance in diverse environmental settings. The results offer valuable insights into the potential of advanced lighting systems in refining the optical identification of plastic bottles, contributing to the advancement of sustainable waste management practices.
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References
Rahmawati, “Perbandingan Penggunaan Polypropilene (Pp) Dan High Density Polyethylene (Hdpe) Pada Campuran Laston_Wc,” J. Media Tek. Sipil, vol. 15, no. 1, p. 11, 2017.
U. B. Surono and I. Ismanto, “The new law journal,” J. Mek. dan Sist. Termal, vol. 1, no. 1, pp. 32–37, 2008.
O. Kehinde, O. J. Ramonu, K. O. Babaremu, and L. D. Justin, “Plastic wastes: environmental hazard and instrument for wealth creation in Nigeria,” Heliyon, vol. 6,no. 10, 2020.
S. R. Ahmad, “A new technology for automatic identification and sorting of plastics for recycling,” Environ. Technol., vol. 25, no. 10, pp. 1143–1149, 2004.
U. B. Surono, “Various Plastic Waste Conversion Methods Become Oil Fuel,” e-journal Janabadra, pp. 32–40, 2014.
E. Scavino, M. A. M. Arebey, H. Basri, A. Hussain, M. A. Hannan, and R. M. Saleh, “A Computer vision based experimental device for plastic bottle identification and sorting,” Civil-Comp Proc., vol. 92, 2009.
Yani and I. Budiman, “Development of identification system of cans and bottle,” J. Phys. Conf. Ser., vol. 622, no. 1, 2015.
R. Munir, Pengantar Pengolahan Citra. Bandung: ITB, 2006.
S. P. Siregar and A. Wanto, “Analysis of Artificial Neural Network Accuracy Using Backpropagation Algorithm In Predicting Process (Forecasting),” IJISTECH (International J. Inf. Syst. Technol., vol. 1, no. 1, p. 34, 2017.
E. P. Cynthia and E. Ismanto, “Jaringan Syaraf Tiruan Algoritma Backpropagation Dalam Memprediksi Ketersediaan Komoditi Pangan Provinsi Riau,” pp. 2579–5406, 2017.
R. E. Gonzalez, Rafael C dan Woods, Digital Image Processing Third Edition, 3rd ed. Pearson Education International, 2018.
G. Kumar and P. K. Bhatia, “A detailed review of feature extraction in image processing systems,” Int. Conf. Adv. Comput. Commun. Technol. ACCT, vol. 5, no. 1, pp. 5–12, 2014.
F. A. I. Achyunda Putra, F. Utaminingrum, and W. F. Mahmudy, “HOG Feature Extraction and KNN Classification for Detecting Vehicle in The Highway,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 14, no. 3, p. 231, 2020.
