Improving defect inspection quality of deep-learning network in dense beans by using hough circle transform for coffee industry

Cheng Ju Kuo, Chao Chun Chen, DIng Chau Wang, Tzu Ting Chen, Yung Chien Chou, Mao Yuan Pai, Gwo Jiun Horng, Min Hsiung Hung, Yu Chuan Lin, Tz Heng Hsu

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

10 Citations (Scopus)

Abstract

In this paper, we propose a novel Hough circle-assisting deep-network inspection scheme (HCADIS), aiming at identifying defects in dense coffee beans. The proposed HCADIS plays a critical role in a camera-based defect removal system to collect defective bean positions for picking all defects off. The idea of the HCADIS is to mix intermediate data from a deep network and a feature engineering method call Hough circle transform for utilizing advantages of both methods in inspecting beans. The Hough circle transform is adopted because it performs quite stable and bean shapes are highly close to circles in nature. A set of core mechanisms are designed for collaboration between the deep network and the Hough circle transform for precisely and accurately inspecting defective beans. Finally, we implement a prototype of the HCADIS and conduct experiments for testing the proposed scheme. The test results reveal that the HCADIS indeed successfully inspect defects among dense beans with superior performance in various metrics. This work provides industrial participants useful experiences for creating deep-learning solutions to bean products in coffee industries.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages798-805
Number of pages8
ISBN (Electronic)9781728145693
DOIs
Publication statusPublished - 2019 Oct
Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
Duration: 2019 Oct 62019 Oct 9

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2019-October
ISSN (Print)1062-922X

Conference

Conference2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
Country/TerritoryItaly
CityBari
Period19-10-0619-10-09

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

Fingerprint

Dive into the research topics of 'Improving defect inspection quality of deep-learning network in dense beans by using hough circle transform for coffee industry'. Together they form a unique fingerprint.

Cite this