NDLI: Video Grading of Oranges in Real-Time

Content Provider	Springer Nature Link
Author	Recce, Michael Plebe, Alessio Tropia, Giuseppe Taylor, John
Copyright Year	1998
Abstract	We describe a novel system for grading oranges into three quality bands, according to their surface characteristics. The system is designed to process fruit with a wide range of size (55–100 mm), shape (spherical to highly eccentric), surface coloration and defect markings. This application requires both high throughput (5–10 oranges per second) and complex pattern recognition. The grading is achieved by simultaneously imaging each item of fruit from six orthogonal directions as it is propelled through an inspection chamber. In order to achieve the required throughput, the system contains state-of-the-art processing hardware, a novel mechanical design, and three separate algorithmic components. One of the key improvements in this system is a method for recognising the point of stem attachment (the calyx) so that it can be distinguished from defects. A neural network classifier on rotation invariant transformations (Zernike moments) is used to recognise the radial colour variation that is shown to be a reliable signature of the stem region. The succession of oranges processed by the machine constitute a pipeline, so time saved in the processing of defect free oranges is used to provide additional time for other oranges. Initial results are presented from a performance analysis of this system.
Starting Page	117
Ending Page	136
Page Count	20
File Format	PDF
ISSN	02692821
Journal	Artificial Intelligence Review
Volume Number	12
Issue Number	1-3
e-ISSN	15737462
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	1998-01-01
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Computer Science Artificial Intelligence (incl. Robotics) Nonlinear Dynamics, Complex Systems, Chaos, Neural Networks
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Linguistics and Language

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