Use of computer image analysis methods to evaluate the quality topping sugar beets with using artificial neural networks

G. Niedbała; N. Mioduszewska; W. Mueller; P. Boniecki; D. Wojcieszak; K. Koszela; S. Kujawa; R. J. Kozłowski; K. Przybył

doi:10.1117/12.2244875

29 August 2016 Use of computer image analysis methods to evaluate the quality topping sugar beets with using artificial neural networks

G. Niedbała; N. Mioduszewska; W. Mueller; P. Boniecki; D. Wojcieszak; K. Koszela; S. Kujawa; R. J. Kozłowski; K. Przybył;

Author Affiliations +

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100332M (2016) https://doi.org/10.1117/12.2244875
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

The aim of the study was create a new, non-invasive method of assessing the quality of sugar beet topping using computer image analysis and artificial neural networks. In paper was carried out the analysis the methods used so far to topping assessment of roots and analysis of the possibilities of using the new proposed method. Classical methods allow an assessment only after harvest of roots (after pull out roots), and the proposed method enables the assessment before harvesting sugar beets. The study used 50 images of topped sugar beet roots, which have been subjected to computer analysis in order to improve the image contrast and brightness. The image was converted from color to images in grayscale, and was carried out segmentation and morphological transformations. Binary image was used to determine the surface area and root circuit and topping circiut. This information was used as input to the neural network, which was expanded to two features, ie. the ratio of the areas and circuits. On the output of the network was information about the topping in the form 0 and 1. Created neural network MLP 6:6-26-1:1 allowed for a sensitivity analysis, which returned information about two important features independent, ie. the surface area of the root and root surface area to topping. The analysis found that it is possible to use methods of computer image analysis for non-invasive assessment of the quality topping sugar beets.

Citation Download Citation

G. Niedbała, N. Mioduszewska, W. Mueller, P. Boniecki, D. Wojcieszak, K. Koszela, S. Kujawa, R. J. Kozłowski, K. Przybył, "Use of computer image analysis methods to evaluate the quality topping sugar beets with using artificial neural networks", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100332M (29 August 2016); doi: 10.1117/12.2244875; https://doi.org/10.1117/12.2244875

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years