Small digital recognition in gravel aggregate production scenario

DOI

10.2991/iceti-16.2016.36How to use a DOI?

Keywords

Small Digital Recognition, Dissimilarity Characteristic, Cascade Identification, Structure Characteristics, HOG

Abstract

The production process of aggregate industrial is monitored by the identification of the digital. In the video, the digital character whose size is less than 12 15(The width of the digital image is 12 pixels, and the height is 15 pixels.) is defined as the small digital. The recognition effect is evaluated by the recognition rate and speed. Because of the small digital of pixels in the video, the numerical recognition algorithm based on template matching is not ideal for the small digital recognition. In order to solve this problem, this paper presents a special number of cascaded recognition process. Firstly, the SVM classifier based on HOG features is used to recognize the number of images, and the special digital of the identification results is based on the two level recognition. Compared with the traditional template matching method, this method can improve the respective average recognition rate of the small digital in production and shipment of two scenarios by 27.36% and 5.05%.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ling Li
AU  - Kai Liu
AU  - Fei Cheng
AU  - Long Li
PY  - 2016/03
DA  - 2016/03
TI  - Small digital recognition in gravel aggregate production scenario
BT  - Proceedings of the 2016 International Conference on Engineering and Technology Innovations
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceti-16.2016.36
DO  - 10.2991/iceti-16.2016.36
ID  - Li2016/03
ER  -