Abstract
Considering the difficulty of fruit and vegetable images with uneven illumination and uncontrolled backgrounds, this paper proposed an image preprocess algorithm based on visual subject detection. Firstly, we can use manifold ranking to significance test and to acquire significance images, then use gradient images and position weighting to get cutting images, finally adjust the image brightness and remove image noise to complete the image preprocessing. The experiment results demonstrated the robustness and real-time of the proposed algorithm which can segment images accurately and the accuracy is higher than 91%.
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
References
Masdiyasa, I.G.S., Purnama, I.K.E., Purnomo, M.H.: Teratozoospermia classification based on the shape of sperm head using OTSU threshold and decision tree (2016)
Yanqing, W., Deyun, C., Chaoxia, S.: Vision-based road detection by Monte Carlo method. Sci. Alert: Inf. Technol. J. 9(3), 481–487 (2010)
Yang, C., Zhang, L., Lu, H., et al.: Saliency detection via graph-based manifold ranking, pp. 3166–3173 (2013)
Buades, A., Coll, B., Morel, J.M.: Image data processing method by reducing image noise, and camera integrating means for implementing said method. EP Patent 1,749,278, 7 Feb 2007
Wang, Y.Q., Zhuang, L.L., Xia, S.C.: Construction research on multi-threshold segmentation based on improved Otsu threshold method. In: 4th International Conference on Automation, Communication, Architectonics and Materials, ACAM, Advanced Materials Research, vol. 1046, pp. 425–428 (2014)
Wang, Y., Wang, Y., Shi, C., Shi, H.: Research on feature fusion technology of fruit and vegetable image recognition based on SVM. In: Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, pp. 591–599 (2016)
Acknowledgment
This work has been supported by the Jiangsu Engineering Research Center for Networking of Elementary Education Resources (grant number: BM2013123).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wang, Y., Zheng, H. (2017). Research on Target Extraction Technology of Fruit and Vegetable Images in the Complex Environment. In: Zou, B., Li, M., Wang, H., Song, X., Xie, W., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-6385-5_59
Download citation
DOI: https://doi.org/10.1007/978-981-10-6385-5_59
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-6384-8
Online ISBN: 978-981-10-6385-5
eBook Packages: Computer ScienceComputer Science (R0)