Vision-based algorithm for recyclable waste classification
Date of Publication
2014
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Electronics and Communications Engineering
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Aaron Don M. Africa
Defense Panel Chair
Melvin K. Cabatuan
Defense Panel Member
Enrique M. Manzano
Carlo E. Ochotorena
Abstract/Summary
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).
Abstract Format
html
Language
English
Format
Accession Number
TU18767
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
668, 6 unnumbered leaves : illustrations (some colored) ; 28 cm.
Recommended Citation
Labay, N. J., Ong, M. B., Sales, J. J., & Toyoda, M. E. (2014). Vision-based algorithm for recyclable waste classification. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/10966
