Segregation of Single Use Plastic by Image Processing

In presentscenario single use plastic pollution Become a major impact on land environment, only 10% of single use plastic has been recycled and the Major task for recycling is segregation especially Single use plastics(75-120) microns has become a Challenging task.The sorting of materials is part of the waste management and recycling processes.The manual sorting is tedious and expensive.Dueto a lack of segregation, especially single-use plastics are dumped in landfills,which cause micropollutants the dry waste which is collected from sanitary workersare transferred to MRF(materials recovery facility)in MRF station mostly they are 8-12 workers segregating the dry waste, They are spending nearly 6hours for segregation, to segregate single use plastic due to spending More hours in segregation the rag pickers easilyaffected by many respiratory problems.This Project propose the analyzing the single use plastics which will use in segregation.So that is why we need to create automated waste deduction through image processing to improve waste segregation of single-use plastic and sorting efficiency.The project proposed a method for automatic plastic segregation.The convolutional neural network used to classify single-use plastics and other plastic wastes.