Study on video text processing

Author

Zhao, Tianxue ; Sun, Guangmin ; Zhang, Cheng ; Chen, Deming

Author_Institution

Dept. of Electron. Eng., Beijing Univ. of Technol., Beijing

fYear

2008

fDate

June 30 2008-July 2 2008

Firstpage

1215

Lastpage

1218

Abstract

This paper adopts combination of DWT and neural network methods to locate the text region. After analyzing the characteristic of video text, the feature of kurtosis is first used in the field of text extraction, which improves the locating accuracy considerably. The OCR accuracy is also improved by using the Shannon interpolation method and Niblack adaptive thresholding method to enhance the video text extracted. Experiments show the methods mentioned above improve the locating accuracy to about 90.4% and the OCR accuracy to about 85.1%.

Keywords

discrete wavelet transforms; interpolation; neural nets; optical character recognition; text analysis; video signal processing; DWT; Niblack adaptive thresholding method; OCR; Shannon interpolation; kurtosis; neural network method; text extraction; video text processing; Content based retrieval; Data mining; Discrete wavelet transforms; Feature extraction; Frequency; Image processing; Interpolation; Neural networks; Optical character recognition software; Text processing; DWT; RBF; Shannon interpolation; improved Niblack adaptive thresholding; kurtosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2008. ISIE 2008. IEEE International Symposium on

Conference_Location

Cambridge

Print_ISBN

978-1-4244-1665-3

Electronic_ISBN

978-1-4244-1666-0

Type

conf

DOI

10.1109/ISIE.2008.4677025

Filename

4677025