Application of Histogram of Oriented Gradients and Local Binary Pattern in Automatic Waste Management Bins

A. Rajagopal, S. Advaith Koushik, Ajay Chandru, Alishan Aziz

    Research output: Chapter in Book/Conference paperConference paper

    Abstract

    Existing waste segregation and management systems that use image processing predominantly work on stationery waste, focusing either on using conveyor belts or on industrial-scale processes. In this work, a household bin that opens, closes and handles waste automatically with minimum human intervention is designed. The goal here is to use image processing with machine learning (ML) algorithms to accurately detect the kind of waste being brought to the bin and trigger a subsequent appropriate set of protocols. This paper investigates the applicability of the following ML algorithms in image processing: Hu Moments, Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP). All three are compared and reasons for selecting one, or more than one in combination, over the other are discussed.

    Original languageEnglish
    Title of host publicationProceedings of the 2nd International Conference on Inventive Research in Computing Applications, ICIRCA 2020
    Place of PublicationUSA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1122-1127
    Number of pages6
    ISBN (Electronic)9781728153742
    DOIs
    Publication statusPublished - Jul 2020
    Event2nd International Conference on Inventive Research in Computing Applications, ICIRCA 2020 - Coimbatore, India
    Duration: 15 Jul 202017 Jul 2020

    Publication series

    NameProceedings of the 2nd International Conference on Inventive Research in Computing Applications, ICIRCA 2020

    Conference

    Conference2nd International Conference on Inventive Research in Computing Applications, ICIRCA 2020
    CountryIndia
    CityCoimbatore
    Period15/07/2017/07/20

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