TY - GEN
T1 - Comparison on eggplant fruit grading between nir-color camera and color camera
AU - Chong, V. K.
AU - Kondo, N.
AU - Ninomiya, K.
AU - Monta, M.
AU - Namba, K.
PY - 2004/12/1
Y1 - 2004/12/1
N2 - An eggplant grading system was introduced in a JA (agricultural cooperative association) at Okayama, 2002. 6 CCD color cameras were installed to evaluate fruit appearance (fruit color, size, shape, bruise, and diseases), before and after turning over in a line and connected to 2 PCs through 6 image grabber boards, Physical properties of the fruits such as fruit length, average, maximum, and minimum diameters, area, apparent volume, fruit color, calyx color, fruit shape, degree of fruit bend, bruise number, bruise area, and so on were extracted from the images. The 6 CCD color cameras were divided into 2 units, which consisted of 3 cameras each set, were installed for complete surface inspection. However it is not easy to detect several kinds of defects on eggplant fruit surface because the fruit has very dark purple color and several defects are very similar colors with normal skin. In this paper, a new color camera whose sensitivity ranges from visible region to infrared region was used. Most of the fruits have higher spectral reflectance in infrared region (700-1200nm). The color CCD camera had the same G and B components with usual color camera, but R signal includes infrared region was specially ordered. Although a color balance among R, G, and B is lost, it was considered that slight color changes of defects and discrimination from dark background were easier than the usual color CCD camera. HSI and chromaticity conversions were tested as a preprocessing to detect various defects. With the improvement on the detections of bruises and defects, this will further increase the effectiveness of the current eggplant-grading machine.
AB - An eggplant grading system was introduced in a JA (agricultural cooperative association) at Okayama, 2002. 6 CCD color cameras were installed to evaluate fruit appearance (fruit color, size, shape, bruise, and diseases), before and after turning over in a line and connected to 2 PCs through 6 image grabber boards, Physical properties of the fruits such as fruit length, average, maximum, and minimum diameters, area, apparent volume, fruit color, calyx color, fruit shape, degree of fruit bend, bruise number, bruise area, and so on were extracted from the images. The 6 CCD color cameras were divided into 2 units, which consisted of 3 cameras each set, were installed for complete surface inspection. However it is not easy to detect several kinds of defects on eggplant fruit surface because the fruit has very dark purple color and several defects are very similar colors with normal skin. In this paper, a new color camera whose sensitivity ranges from visible region to infrared region was used. Most of the fruits have higher spectral reflectance in infrared region (700-1200nm). The color CCD camera had the same G and B components with usual color camera, but R signal includes infrared region was specially ordered. Although a color balance among R, G, and B is lost, it was considered that slight color changes of defects and discrimination from dark background were easier than the usual color CCD camera. HSI and chromaticity conversions were tested as a preprocessing to detect various defects. With the improvement on the detections of bruises and defects, this will further increase the effectiveness of the current eggplant-grading machine.
KW - Eggplant
KW - Grading
KW - Machine vision
KW - Quality evaluation
KW - Spectral reflectance
KW - TV camera
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M3 - Conference contribution
AN - SCOPUS:27844478856
SN - 189276945X
SN - 9781892769459
T3 - Proceedings of the International Conference on Automation Technology for Off-road Equipment, ATOE 2004
SP - 387
EP - 393
BT - Automation Technology for Off-road Equipment - Proceedings of the International Conference, ATOE 2004
A2 - Zhang, Q.
A2 - Iida, M.
A2 - Mizushima, A.
T2 - International Conference on Automation Technology for Off-road Equipment, ATOE 2004
Y2 - 7 October 2004 through 8 October 2004
ER -