Vision-based algorithm for recyclable waste classification
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Article
Source Title
ARPN Journal of Engineering and Applied Sciences
Volume
14
Issue
13
First Page
2459
Last Page
2463
Publication Date
7-1-2019
Abstract
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).
html
Recommended Citation
Africa, A. M., Labay, N. J., Ong, M. B., Sales, J. J., & Toyoda, M. E. (2019). Vision-based algorithm for recyclable waste classification. ARPN Journal of Engineering and Applied Sciences, 14 (13), 2459-2463. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/2453
Disciplines
Electrical and Computer Engineering
Keywords
Refuse and refuse disposal; Recycling (Waste, etc.); Image processing; Computer vision
Upload File
wf_no