A Skew Detection Method for 2D Bar Code Images Based on the Least Square Method

Author

Liang, Ying-hong ; Wang, Zhi-Yan

Author_Institution

Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

3974

Lastpage

3977

Abstract

A robust and fast algorithm for skew detection in 2D bar code images is proposed in this paper. It is based on the least square method. Unlike the methods based on Hough transforms that are computationally expensive, it quickly obtains skew angles making it applicable to real-time applications. This method includes two processes, the segmenting process searches for the bar code region, and then the line fitting process fits the borderline and obtains the skew angle. Experimental results show this method reduces the running time

Keywords

Hough transforms; bar codes; image recognition; image segmentation; least mean squares methods; 2D bar code images; Hough transforms; least square method; skew detection method; Background noise; Clustering methods; Computer science; Cybernetics; Design methodology; Fourier transforms; Image converters; Image processing; Image segmentation; Least squares methods; Machine learning; Machine learning algorithms; Nearest neighbor searches; Robustness; 2D bar code; Hough transform; Least square method; Skew detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258793

Filename

4028766