Literature DB >> 22748840

A new technique for detecting colored macro plastic debris on beaches using webcam images and CIELUV.

Tomoya Kataoka1, Hirofumi Hinata, Shin'ichiro Kako.   

Abstract

We have developed a technique for detecting the pixels of colored macro plastic debris (plastic pixels) using photographs taken by a webcam installed on Sodenohama beach, Tobishima Island, Japan. The technique involves generating color references using a uniform color space (CIELUV) to detect plastic pixels and removing misdetected pixels by applying a composite image method. This technique demonstrated superior performance in terms of detecting plastic pixels of various colors compared to the previous method which used the lightness values in the CIELUV color space. We also obtained a 10-month time series of the quantity of plastic debris by combining a projective transformation with this technique. By sequential monitoring of plastic debris quantity using webcams, it is possible to clean up beaches systematically, to clarify the transportation processes of plastic debris in oceans and coastal seas and to estimate accumulation rates on beaches.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Mesh:

Substances:

Year:  2012        PMID: 22748840     DOI: 10.1016/j.marpolbul.2012.06.006

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  3 in total

1.  Semi-automatic recognition of marine debris on beaches.

Authors:  Zhenpeng Ge; Huahong Shi; Xuefei Mei; Zhijun Dai; Daoji Li
Journal:  Sci Rep       Date:  2016-05-09       Impact factor: 4.379

2.  Delineating and preventing plastic waste leakage in the marine and terrestrial environment.

Authors:  John N Hahladakis
Journal:  Environ Sci Pollut Res Int       Date:  2020-03-02       Impact factor: 4.223

3.  Quantification of floating riverine macro-debris transport using an image processing approach.

Authors:  Tomoya Kataoka; Yasuo Nihei
Journal:  Sci Rep       Date:  2020-02-10       Impact factor: 4.379

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.