Vision-based algorithm for recyclable waste classification

• Main Authors: Africa, Aaron Don M., Labay, Neil Patrick J., Ong, Mariel Sheryn B., Sales, Jillian Abigail J., Toyoda, Mitsuru Mike E.
• Format: text
• Published: Animo Repository 2019
• Subjects: Refuse and refuse disposal; Recycling (Waste, etc.); Image processing; Computer vision; Electrical and Computer Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2453
• Institution: De La Salle University

Waste segregation is one of the most prominent problem in the world particularly in the Philippines where waste segregation is done manually. This research aims to solve the problem regarding waste segregation by means of image processing. These recyclable materials are classified into nine groups namely: aerosol cans, aluminum cans, cereal box, glass bottles, paper bowls, plastic bottles, plastic cups, tetra packs and tin cans. The recyclable material is subjected to a controlled environment then the image is captured by the camera. The region of interest is extracted from the image by the use of cascade filters such as weiner and median filter along with morphological operators and canny edge detecto. Scale Invariant Feature Transform (SIFT) features are extracted from the image. Then two methods are used for classfying, namely: Random Sampling and Consensus (RanSac) and a combination of Bag-of-Words (BOW) and Support Vector Machines (SVM). © 2006-2019 Asian Research Publishing Network (ARPN).