TY - JOUR
T1 - Features extraction for eggplant fruit grading system using machine vision
AU - Chong, Vui Kiong
AU - Kondo, Naoshi
AU - Ninomiya, Kazunori
AU - Nishi, Takao
AU - Monta, Mitsuji
AU - Namba, Kazuhiko
AU - Zhang, Qin
PY - 2008/12/1
Y1 - 2008/12/1
N2 - Machine vision based grading for agricultural crops has been well developed and accepted as an attractive grading method. However, machine vision based grading for eggplant fruit is not available yet. This study reports on the attempt to develop an eggplant grading machine using six CCD cameras as the sensing device. Feature extraction algorithms were developed to extract eggplant's features, i.e., length, diameter, volume, curvature, color homogeneity, calyx color, calyx area, and surface defect. The system could acquire six images per fruits covering the entire surface of the eggplant fruits. An agreement rate of 78.0% was achieved in the feasibility study where the machine vision based grading was compared with manual grading. The throughput of the developed system was 0.3 second per fruit. Details of the system, an outline of the algorithm, and performance results are reported in this article.
AB - Machine vision based grading for agricultural crops has been well developed and accepted as an attractive grading method. However, machine vision based grading for eggplant fruit is not available yet. This study reports on the attempt to develop an eggplant grading machine using six CCD cameras as the sensing device. Feature extraction algorithms were developed to extract eggplant's features, i.e., length, diameter, volume, curvature, color homogeneity, calyx color, calyx area, and surface defect. The system could acquire six images per fruits covering the entire surface of the eggplant fruits. An agreement rate of 78.0% was achieved in the feasibility study where the machine vision based grading was compared with manual grading. The throughput of the developed system was 0.3 second per fruit. Details of the system, an outline of the algorithm, and performance results are reported in this article.
KW - Classification
KW - Grading
KW - Image processing
KW - Image segmentation
KW - Machine vision
UR - http://www.scopus.com/inward/record.url?scp=58049220023&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=58049220023&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:58049220023
VL - 24
SP - 675
EP - 684
JO - Applied Engineering in Agriculture
JF - Applied Engineering in Agriculture
SN - 0883-8542
IS - 5
ER -