Title :
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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258793
