A Double Image Acquisition System with Visible and UV LEDs for Citrus Fruit

Journal of Robotics and Mechatronics

Volumn 21, Issue 4, 2009, Pages 533-540

  Kurita, Mitsutaka ^a   Kondo, Naoshi ^b   Shimizu, Hiroshi ^b   Ling, Peter ^c   Falzea, Paolo D ^d   Shiigi, Tomoo ^e   Ninomiya, Kazunori ^g   Nishizu, Takahisa ^f   Yamamoto, Kazuya ^e  

^a SI Seiko Co Ltd   (Japan)

^b KYOTO UNIVERSITY   (Japan)

^c OHIO STATE UNIVERSITY   (United States)

^d UNIVERSITY MEDITERRANEA OF REGGIO CALABRIA   (Italy)

^e EHIME UNIVERSITY   (Japan)

^f GIFU UNIVERSITY   (Japan)

^g NONE

Author keywords

fluorescence; fruit grading; fruit quality; machine vision; post harvest

Indexed keywords

CCD CAMERAS; CITRUS FRUITS; COLOR; COMPUTER VISION; GRADING; IMAGE ACQUISITION; INSPECTION; LIGHT EMITTING DIODES;

COLOR DETECTION; FRUIT GRADING; FRUIT QUALITY; IMAGE ACQUISITION SYSTEMS; MACHINE-VISION; POSTHARVEST; SHAPE DETECTION; SIZE DETECTION; UV LEDS; VISION CAPABILITY;

FLUORESCENCE;

EID: 80051867800     PISSN: 09153942     EISSN: 18838049     Source Type: Journal    
DOI: 10.20965/jrm.2009.p0533     Document Type: Article

References (13)

1. N. Aleixos, J. Blasco, F. Navarron, and E. Molto, “Multispectral inspection of citrus in real-time using machine vision and digital signal,” Computers and Electronics in Agriculture, 33, pp. 121-137, 2002.
2. W. Andrew, “Vision system grades moving food products,” Vision System Design, pp. 26-29, June 2002.
3. A. Davenel, C. Guizard, T. Labarre, and F. Sevila, “Automation Detection of Surface Defects on Fruit by Using a Vision System,” J. agric. Engng Res. 41, pp. 1-9, 1998.
4. T. Ishii, H. Toita, N. Kondo, and N. Tahara, “Deciduous Fruit Grading Robot(Part 2) – Development of Image Processing System –,” J. JSAM, 65(6), pp. 173-183, 2003 (in Japanese).
5. M. Kurita, N. Kondo, and K. Ninomiya, “Defect Detection for Tomato Granding by use of Six Color CCD Cameras,” Journal of Science and High Technology in Agriculture, 18(2), pp. 135-144, 2006.
6. V. Leemans, H. Magein, M. F. Destain, “On-line Fruit Grading ac-cording to their External Quality using Machine Vision,” Biosys-tems Engineering, 83(4), pp. 397-404, 2002.
7. V. Leemans and M. F. Destain, “A real-time grading method of ap-ples based on features extracted from defects,” Journal of Food En-gineering, 61, pp. 83-89, 2004.
8. J. B. Njoroge, K. Ninomiya, N. Kondo, and H. Toita, “Automated Fruit Grading System Using Image,” Proc. 2002 SICE, Osaka, pp. 1290-1295, 2002.
9. Y. Ogawa, N. Kondo, and S. Shibusawa, “Internal Quality Evaluation of Fruit with Soft X-ray CT,” Journal of the JSAM, 67(3), pp. 114-121, 2005.
10. Y. Ogawa, N. Kondo, and S. Shibusawa, “Internal Quality Evaluation of Fruit with Soft Transparent Image,” Journal of Science and High Technology in Agriculture, 17(2), pp. 75-83, 2005.
11. R.Lu and D.Ariana, “A near-Infrared Sensing Technique for Mea-sureing Internal Quality of Apple Fruit,” Applied Engineering in Agriculture, 18(5), pp. 585-590, 2002.
12. J. Uozumi et al., “Spectrophotometric System for the Quality Evaluation of Unevenly Clored Food,” Journal of the JSFST, 34(3), pp. 163-170, 1987.
13. N. Kondo, K. Yamamoto, S. Taniwaki, M. Kuramoto, M. Kurita, and K. Ninomiya, “Machine vision system for detecting rotten citrus fruit by use of UV LEDs,” ASABE an Int. Conf. in BIOLOGICAL SENSORICS, (Database), 2007.