In terms of the requirement of automatically sorting pearls, the pearl contour feature extraction and
shape recognition algorithm are studied in this paper to reckon with the rapid identification of pearls shape online,
and a monocular dynamic machine vision-based pearl shape detection device is designed. Through blowing, the
pearl is suspended in a funnel shaped container and flipped rapidly in the device. The entire surface image of
the pearl to be measured can be promptly grasped by the camera placed right above the funnel. The results
of illumination experiments conducted from different angles indicate that the image contour acquired by the
medium angle illumination is better extracted. The pearl shape test indicates that the method is incorporated
with the inflatable suspension device to classify the pearls into seven types according to the national standard,
and additionally the average error rate is confined under 5.38%. The shape characteristic of the pearl can be
detected promptly and reliably, and accordingly the high-speed automatic sorting can be satisfied.
WANG Yuzong (王毓综), DENG Fei (邓飞), ZHAO Daxu (赵大旭), YE Jiaying (叶佳英), WANG Peixin (王佩欣), SHOU Guozhong (寿国忠)
. Monocular Dynamic Machine Vision-Based Pearl Shape Detection[J]. Journal of Shanghai Jiaotong University(Science), 2019
, 24(5)
: 654
-662
.
DOI: 10.1007/s12204-019-2103-5
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