Pattern recognition for counting of bounded bar steel

Author

Jingzhong, Wang ; Hao, Chen ; Xiaoqing, Xu

Author_Institution

Coll. of Inf. Eng., North China Univ. of Technol., Beijing, China

fYear

2011

Firstpage

173

Lastpage

176

Abstract

Automatic Counting of the bundled bar steel is unsolved. A new segmentation method based on quasi-circular assumption and a new object recognition method based on scanning are present. Owing to the simple addition, subtraction and logic operation, these two methods have real time property. The total CPU time is less than 1 second for an 640*480 pixels image, The experiments show that the new method can segment the aggregated bars effectively, and it can be used to improve the accuracy and the speed of recognizing and countering of irregular and aggregated objects.

Keywords

bars; image segmentation; object recognition; production engineering computing; steel industry; addition operation; bundled bar steel automatic counting; logic operation; object recognition method; pattern recognition; quasi-circular assumption; segmentation method; subtraction operation; Bars; Frequency selective surfaces; Image color analysis; Image recognition; Image segmentation; Shape; Steel; Auto Counting; Bar steel; Concave Point; Image Segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Applications of Digital Information and Web Technologies (ICADIWT), 2011 Fourth International Conference on the

Conference_Location

Stevens Point, WI

Print_ISBN

978-1-4244-9824-6

Type

conf

DOI

10.1109/ICADIWT.2011.6041396

Filename

6041396