Title :
Text Line Detection Based on Mutation Analysis
Author :
Hou Dewen ; Wang Xichang ; Liu Jiang ; Chen Xia
Author_Institution :
Key Lab. for Distrib. Comput. Software, Shandong Normal Univ., Jinan, China
Abstract :
A text line detection method based on wavelet transformation and mutation analysis is proposed in this paper. First the character density image is acquired from the input document image by the project function with strips, and then the density image is analyzed by wavelet transformation where the Gaussian or its derivative function is used as the wavelet basis. The local peak positions indicate the line texture which will be continuous and single pixel. Because of the statistical properties of project function and wavelet transformation of mutations signal detection, this algorithm is not sensitive to noise and warped distortions. Experiments show that this algorithm is accurate and robust.
Keywords :
Gaussian processes; document image processing; image texture; statistical analysis; text detection; wavelet transforms; Gaussian function; character density image; derivative function; input document image; line texture; mutation analysis; mutation signal detection; project function statistical properties; text line detection method; wavelet transformation; Image edge detection; Noise; Signal analysis; Signal detection; Wavelet analysis; Wavelet transforms; mutation signal analysis; project function; text line detection; wavelet transformation;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location :
Shiyang
DOI :
10.1109/ICCIS.2013.184