Vision-based algorithm for recyclable waste classification

• Main Authors: Labay, Neil Patrick J., Ong, Mariel Sheryn B., Sales, Jillian Abigail J., Toyoda, Mitsuru Mike E.
• Format: text
• Language: English
• Published: Animo Repository 2014
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/10966
• 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 materials is subjected to a controlled environment then the image is captured by the camera. By the use of cascade filters such as Wiener and medium filter along with morphological operators and canny edge detector, the region of interest is extracted from the image. Then used two methods of classifying namely: Random Sampling and Consensus (RanSac) and combination of Bag-of-Words (BoW) and Support Vector Machines (SVM).