Abstract
This paper focuses on the character segmentation in the process of food packaging detection. After preprocessing the collected food packaging image, in order to recognize and analyze the characters, it is necessary to segment the string into a single character. In view of the adhesion phenomenon in the process of character segmentation, this paper uses vs2015 development environment and opencv, Eigen and other open source libraries to develop under win10 system, improves the projection segmentation method used in character segmentation in the past, realizes the accurate segmentation of food packaging characters, and lays a good foundation for the next character recognition.
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
Guan, X., Jian, S., Hongda, P., Zhiguo, Z., Haibin, G.: An image enhancement method based on gamma correction. In: 2009 Second International Symposium on Computational Intelligence and Design, pp. 60–63 (2009)
Parker, J.R., Federl, P.: An approach to license plate recognition (1996)
Song, C., Ye, H.: Segmenting characters of license plate based on digital morphology. Optoelectron. Technol. Inf. 18(6), 58–62 (2005)
Jagannathan, J., Sherajdheen, A., Deepak, R.M.V., et al.: License plate character segmentation using horizontal and vertical projection with dynamic thresholding. In: 2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology (ICECCN), pp. 700–705. IEEE (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Jin, S., Jia, T., Zhou, Z., Lu, D., Lin, Q. (2022). Segmentation Method of Food Packaging Inkjet Characters Based on Computer Vision. In: Li, X. (eds) Advances in Intelligent Automation and Soft Computing. IASC 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-81007-8_83
Download citation
DOI: https://doi.org/10.1007/978-3-030-81007-8_83
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-81006-1
Online ISBN: 978-3-030-81007-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)