Survey on Waste Segmentation Using Image Processing

This survey investigates Waste Segmentation using Image Processing, crucial for effective waste management amid global urbanization. It reviews diverse techniques, from traditional methods like thresholding to modern approaches involving machine learning and deep neural networks. The survey emphasizes image preprocessing for enhanced accuracy and identifies challenges like limited datasets. These include integrating multispectral imaging for enhanced discrimination and hybrid methodologies combining traditional techniques with deep learning. The survey's insights serve as a valuable resource for researchers, practitioners, and policymakers, guiding efforts towards sustainable waste management practices amidst rapid urbanization and population growth.