@inproceedings{1406624802b545b9a5238d63943e7aa1,
title = "Improving defect inspection quality of deep-learning network in dense beans by using hough circle transform for coffee industry",
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.",
author = "Kuo, {Cheng Ju} and Chen, {Chao Chun} and Wang, {DIng Chau} and Chen, {Tzu Ting} and Chou, {Yung Chien} and Pai, {Mao Yuan} and Horng, {Gwo Jiun} and Hung, {Min Hsiung} and Lin, {Yu Chuan} and Hsu, {Tz Heng}",
note = "Funding Information: Authors thank Steven Lin with AdvantTech Co. for useful comments on prototype development to meet industrial needs. This work was supported by Ministry of Science and Technology (MOST) of Taiwan under Grants MOST 107-2221-E-006-017-MY2, 108-2221-E-034-015-MY2, 107-2218-E-006-055, 107-2221-E-218-024, and 108-2218-E-020-003. This work was also supported by the “Intelligent Service Software Research Center” in STUST and the “Allied Advanced Intelligent Biomedical Research Center, STUST” under Higher Education Sprout Project, Ministry of Education, Taiwan. This work was financially supported by the “Intelligent Manufacturing Research Center” (iMRC) in NCKU from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education in Taiwan. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 ; Conference date: 06-10-2019 Through 09-10-2019",
year = "2019",
month = oct,
doi = "10.1109/SMC.2019.8914175",
language = "English",
series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "798--805",
booktitle = "2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019",
address = "United States",
}