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Paper Abstract and Keywords
Presentation 2022-02-22 14:40
Detection of Physiological Disorders in European Pear Using HSV Color Features
Noritaka Kubota, Tatsuya Yamazaki (Niigata Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) For the "Le Lectier" (pear), appearance quality is important to determine its grade, and grading based on shipping standards is necessary. However, the workload of grading judgement and the subjective discrimination are problems, and automated and objective discrimination using machines and systems are required to solve the problems. Therefore, in order to develop a pear grading system, a method to detect the appearance quality of pears is investigated. The appearance quality of pears is classified into two major categories: appearance defacement and physiological disorders, and deep learning methods have been used to detect and classify appearance defacement. In this study, we propose a detection method using light image processing based on color features for physiological disorders that have been difficult to annotate due to limited data. The physiological disorders of pears show differences in hue (H), saturation (S) and brightness values (V) in HSV color space compared to normal skin and calyx. The HSV values of these areas are defined as color features, and the physiological disorder areas are detected in the captured images of pears by thresholding using the differences in color features.
Keyword (in Japanese) (See Japanese page) 
(in English) Smart Agriculture / Image Processing / HSV Color Space / Color Feature / European Pear / / /  
Reference Info. ITE Tech. Rep.
Paper #  
Date of Issue  
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Conference Date 2022-02-21 - 2022-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) online 
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Topics (in English)  
Paper Information
Registration To IEICE-IE 
Conference Code 2022-02-IE-ITS-AIT-ME-MMS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Detection of Physiological Disorders in European Pear Using HSV Color Features 
Sub Title (in English)  
Keyword(1) Smart Agriculture  
Keyword(2) Image Processing  
Keyword(3) HSV Color Space  
Keyword(4) Color Feature  
Keyword(5) European Pear  
1st Author's Name Noritaka Kubota  
1st Author's Affiliation Niigata University (Niigata Univ.)
2nd Author's Name Tatsuya Yamazaki  
2nd Author's Affiliation Niigata University (Niigata Univ.)
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Date Time 2022-02-22 14:40:00 
Presentation Time 15 
Registration for IEICE-IE 
Paper #  
Volume (vol) ITE-46 
Number (no)  
#Pages ITE- 
Date of Issue  

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