Mackerel Classification Using Global and Local Features

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Blue and chub mackerels are often caught at the same time, and their market prices are different. Thus, humans need to classify them by their hands. Therefore, the demand for automatic sorting machines of these mackerels using image processing technique is increasing. Classification for blue and chub mackerels is a challenging task due to their quite similar appearance. In this paper, we propose a method for classifying blue and chub mackerels by image processing technique. The difference of the two mackerels appears on the whole and the local specific parts. Therefore, we use global and local features that are extracted from the whole and the specific part in fish images, respectively. Experimental results showed that the proposed method is superior to the methods using only global or local feature.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation, ETFA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1209-1212
Number of pages4
ISBN (Electronic)9781538671085
DOIs
Publication statusPublished - 2018 Oct 22
Event23rd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2018 - Torino, Italy
Duration: 2018 Sep 42018 Sep 7

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2018-September
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Other

Other23rd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2018
Country/TerritoryItaly
CityTorino
Period18/9/418/9/7

Keywords

  • blue mackerel
  • chub mackerel
  • fish classification
  • global feature
  • image processing
  • local feature

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Computer Science Applications

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