A Comparative Study to find an Effective Image Segmentation Technique using Clustering to obtain the Defective Portion of an Apple

Namrata Varad Mhapne, S. V. Harish, Anita S. Kini, V. G. Narendra

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

Abstract

This paper aims at quality evaluation of the apple fruit to identify the surface defects based on the application of image processing and the computer vision systems. The external appearance of a fruit is one of the most important quality features and the manual assessment of the same by the human inspectors is costly, highly variable and inconsistent. Hence to meet the ever-increasing demand for the uniform and high-quality fruits, an automated visual inspection technique using computer vision and image processing will undoubtedly be the preferred method. A crucially significant process for the automated fruit grading system is image segmentation. A comparative end result of the segmentation techniques based on the concept of clustering to find the defective portion of the apple fruit is presented. The motivation behind the proposed method is to improve the time complexity and accuracy of the clustering technique with the use of preprocessing.

Original languageEnglish
Title of host publication2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages304-309
Number of pages6
ISBN (Electronic)9781538680100
DOIs
Publication statusPublished - 01-04-2019
Event2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019 - London, United Kingdom
Duration: 24-04-201926-04-2019

Publication series

Name2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019

Conference

Conference2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019
CountryUnited Kingdom
CityLondon
Period24-04-1926-04-19

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Artificial Intelligence
  • Management of Technology and Innovation
  • Computer Science Applications
  • Information Systems and Management
  • Control and Optimization
  • Instrumentation

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  • Cite this

    Mhapne, N. V., Harish, S. V., Kini, A. S., & Narendra, V. G. (2019). A Comparative Study to find an Effective Image Segmentation Technique using Clustering to obtain the Defective Portion of an Apple. In 2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019 (pp. 304-309). [8776751] (2019 International Conference on Automation, Computational and Technology Management, ICACTM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACTM.2019.8776751