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Proceedings Paper

The positioning algorithm based on feature variance of billet character
Author(s): Jiansong Yi; Hanyu Hong; Yu Shi; Hongyang Chen
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Paper Abstract

In the process of steel billets recognition on the production line, the key problem is how to determine the position of the billet from complex scenes. To solve this problem, this paper presents a positioning algorithm based on the feature variance of billet character. Using the largest intra-cluster variance recursive method based on multilevel filtering, the billet characters are segmented completely from the complex scenes. There are three rows of characters on each steel billet, we are able to determine whether the connected regions, which satisfy the condition of the feature variance, are on a straight line. Then we can accurately locate the steel billet. The experimental results demonstrated that the proposed method in this paper is competitive to other methods in positioning the characters and it also reduce the running time. The algorithm can provide a better basis for the character recognition.

Paper Details

Date Published: 14 December 2015
PDF: 9 pages
Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 981203 (14 December 2015); doi: 10.1117/12.2205742
Show Author Affiliations
Jiansong Yi, Wuhan Institute of Technology (China)
Hanyu Hong, Wuhan Institute of Technology (China)
Yu Shi, Wuhan Institute of Technology (China)
Hongyang Chen, Wuhan Institute of Technology (China)

Published in SPIE Proceedings Vol. 9812:
MIPPR 2015: Automatic Target Recognition and Navigation
Nong Sang; Xinjian Chen, Editor(s)

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