Identification of fruit size and maturity through fruit images using OpenCV-Python and Rasberry Pi

Color and size are one of the most important features for accurate maturity classification of fruits. Small business farmers use manual evaluation through visual observation to classify the maturity of their pick. which according to FAMA there are six maturity indexes. The repetitive process is tedi...

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Veröffentlicht in:2017 International Conference on Robotics, Automation and Sciences (ICORAS) S. 1 - 3
Hauptverfasser: Mustaffa, Izadora Binti, Khairul, Syawal Fikri Bin Mohd
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.11.2017
Schlagworte:
Clustering algorithms
color index
Computer vision
fruit maturity
fruit size
Histograms
Image color analysis
Indexes
OpenCV-Python
Rasberry Pi
Size measurement
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Zusammenfassung:Color and size are one of the most important features for accurate maturity classification of fruits. Small business farmers use manual evaluation through visual observation to classify the maturity of their pick. which according to FAMA there are six maturity indexes. The repetitive process is tedious and is prone to human error. This paper focuses on the identification of maturity of mango fruit. Raspberry Pi is a small computer, which is powerful enough to run an image processing algorithm is chosen for this system. The developed image processing algorithm is able to determine the size of the fruit and apply the K-means clustering to determine the fruit color.
DOI:10.1109/ICORAS.2017.8308068