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  1. NTU Scholars
  2. 生物資源暨農學院
  3. 生物機電工程學系
Please use this identifier to cite or link to this item: https://scholars.lib.ntu.edu.tw/handle/123456789/362587
Title: Automatic X-ray quarantine scanner and pest infestation detector for agricultural products
Authors: Chuang, C.-L.
Ouyang, C.-S.
Lin, T.-T.
Yang, M.-M.
Yang, E.-C.
Huang, T.-W.
Kuei, C.-F.
Luke, A.
Jiang, J.-A.
JOE-AIR JIANG 
EN-CHENG YANG 
TA-TE LIN 
Keywords: Agricultural products; LabVIEW; Pest inspection; Quarantine; X-ray imaging technique
Issue Date: 2011
Journal Volume: 77
Journal Issue: 1
Start page/Pages: 41-59
Source: Computers and Electronics in Agriculture 
Abstract: 
This paper presents a new automatic and effective quarantine system for detecting pest infestation sites in agricultural products, e.g. fruits. This work integrated mechanical design, mechatronics instrumentation, X-ray and charge-coupled device (CCD) image acquisition devices, LabVIEW-based analysis and control software, and image diagnosis algorithms into the automatic X-ray quarantine scanner system. Based on the LabVIEW development platform, a friendly graphical user interface (GUI) was designed for assisting the operations of quarantine scanner system. To enhance the accuracy and efficiency of pest quarantine process, a control scheme for performing start-up procedure of the system, parameter setting and calibration of the X-ray source and line-scan sensor, and automatic inspection for pest were developed. A novel pest infestation detector consisted of image processing algorithms were also proposed to aid the operator in identifying possibly infested fruits. The image processing procedures include contrast enhancement, median filtering, mathematical morphology operators, and adaptive thresholding by statistical z-test for identifying the infested sites of fruit on an X-ray image. Experimental results show that the X-ray quarantine scanner and pest infestation detector are able to locate the infested sites with highly successful rate up to 94% on the 4th day after eggs implanted. Furthermore, both intact and egg-implanted fruits were used to evaluate the sensitivity, specificity, accuracy, and precision of the proposed system. The evaluation results are respectively 96.8%, 98.6%, 97.7%, and 98.7%, which are significantly better than traditional visual inspection. © 2011 Elsevier B.V.
URI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79957731209&partnerID=MN8TOARS
http://scholars.lib.ntu.edu.tw/handle/123456789/362587
DOI: 10.1016/j.compag.2011.03.007
SDG/Keyword: Acquisition device; Adaptive thresholding; Automatic inspection; Contrast Enhancement; Control schemes; Control software; Development platform; Evaluation results; Image diagnosis; Image processing algorithm; LabViEW; Mechanical design; Median filtering; Parameter setting; Pest infestation; Pest inspection; Processing procedures; Quarantine; Scanner systems; Start-up procedure; Visual inspection; X-ray image; X-ray imaging technique; X-ray sources; Agricultural products; Algorithms; Computer programming languages; Detectors; Fruits; Graphical user interfaces; Image acquisition; Imaging systems; Inspection; Mathematical morphology; Mathematical operators; X ray analysis; X ray apparatus; X rays; Scanning; accuracy assessment; agricultural production; algorithm; calibration; electronic equipment; fruit; pest control; quarantine; software
[SDGs]SDG2
Appears in Collections:生物機電工程學系

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臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

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