This paper presents methods to identify the plastic waste based on its resin identification code to provide an efficient recycling of post-consumer plastic waste. We propose the design, training and testing of different machine learning techniques to (i) identify a plastic waste that belongs to the known categories of plastic waste when the system is trained and (ii) identify a new plastic waste that do not belong the any known categories of plastic waste while the system is trained. For the first case,we propose the use of one-shot learning techniques using Siamese and Triplet loss networks. Our proposed approach does not require any augmentation to increase the size of the database and achieved a high accuracy of 99.74%. For the second case, we propose the use of supervised and unsupervised dimensionality reduction techniques and achieved an accuracy of 95% to correctly identify a new plastic waste.
@article{arxiv.2011.07747,
title = {Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code},
author = {Shivaank Agarwal and Ravindra Gudi and Paresh Saxena},
journal= {arXiv preprint arXiv:2011.07747},
year = {2020}
}