Design and Performance of an Automatic Egg Sorting System Based on Computer Vision
Design and Performance of an Automatic Egg Sorting System Based on Computer Vision
Author(s): Jakhfer Alikhanov, Stanislav M. Penchev, Tsvetelina D. Georgieva, Aidar Moldazhanov, Akmaral Kulmakhambetova, Zhandos Shynybay, Emil Stefanov, Plamen I. DaskalovSubject(s): ICT Information and Communications Technologies
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Eggs sorting; computer vision; real – time inspection
Summary/Abstract: An automatic system for eggs sorting by indirect weight and shape assessment using computer vision is presented in the paper. Some basic geometric parameters of the eggs, namely: minor and major axis, area and perimeter, shape factor and shape index, are obtained using image processing algorithms. The weight is assessed from the geometric parameters using a regression model. The sorting accuracy of the proposed system is evaluated for two transport conveyors speeds, corresponding to 2 and 3 eggs per second. It is found that the overall sorting accuracy in each case is 94.6% and 90.3% respectively.
Journal: TEM Journal
- Issue Year: 8/2019
- Issue No: 4
- Page Range: 1319-1325
- Page Count: 7
- Language: English