Abstract
In the following paper, the results of studies on the impact of lighting configuration on the quality of seed detection in cherries have been presented. The general concept of a vision system for cherry pits detection has been proposed. The two types of light were considered and characterized. The results of cherry classification confirm the effectiveness of the proposed solution and allow to indicate a better solution.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Qin, J., Lu, R.: Detection of pits in tart cherries by hyperspectral transmission imaging. Trans. ASAE 48, 1963–1970 (2005)
Siedliska, A., Zubik, M., Baranowski, P., Mazurek, W.: Algorithms for detecting cherry pits on the basis of transmittance mode hyperspectral data. Int. Agrophys. 31, 539–549 (2017)
Donis-Gonzǎlez, I.R., Guyer, D.E., Kavdir, I., Shahriari, D., Pease, A.: Development and applicability of an agarose-based tart cherry phantom for computer tomography imaging. J. Food Meas. Charact. 9(3), 290–298 (2015)
Kawano, S.: Past, present and future near infrared spectroscopy applications for fruit and vegetables. NIR News 27(1), 7–9 (2016)
Lu, Y., Huang, Y., Lu, R.: Innovative hyperspectral imaging-based techniques for quality evaluation of fruits and vegetables: a review. Appl. Sci. 7(2), 189 (2017)
Muresan, H., Oltean, M.: Fruit recognition from images using deep learning (2018)
Yeong, T.J., Jern, K.P., Yao, L.K., Hannan, M.A., Hoon, H.T.G.: Applications of photonics in agriculture sector: a review. Open Access Mol. 24(10), 24 (2019)
Meruliya, T., Dhameliya, P., Jainish, P., Dilav, P., Pooja, K., Sapan, N.: Image processing for fruit shape and texture feature extraction - review. Int. J. Comput. Appl. 129, 30–33 (2015)
Bhargava, A., Bansal, A.: Fruits and vegetables quality evaluation using computer vision: a review. J. King Saud Univ. - Comput. Inf. Sci. (2018)
Gongal, A.A., Karkee, S., Manoj Zhang, Q., Lewis, K.: Sensors and systems for fruit detection and localization: a review. Cmput. Electron. Agric. 116, 8–19 (2015)
Hameed, K., Chai, D., Rassau, A.: A comprehensive review of fruit and vegetable classification techniques. Image Vis. Comput. 80, 24–44 (2018)
Acknowledgement
This work was supported by the National Centre for Research and Development, project POIR.01.01.01-00-1045/17.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Garbat, P., Sadura, P., Olszewska, A., Maciejewski, P. (2020). Vision System for Pit Detection in Cherries. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications. IP&C 2019. Advances in Intelligent Systems and Computing, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-31254-1_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-31254-1_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31253-4
Online ISBN: 978-3-030-31254-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)