Texture-Based Approach for Text Detection in Images Using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm

Abstract

The current paper presents a novel texture-based method for detecting texts in images. A support vector machine (SVM) is used to analyze the textural properties of texts. No external texture feature extraction module is used; rather, the intensities of the raw pixels that make up the textural pattern are fed directly to the SVM, which works well even in… (More)
DOI: 10.1109/TPAMI.2003.1251157

Topics

12 Figures and Tables

Statistics

02040'05'06'07'08'09'10'11'12'13'14'15'16'17'18
Citations per Year

335 Citations

Semantic Scholar estimates that this publication has 335 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Kim2003TextureBasedAF, title={Texture-Based Approach for Text Detection in Images Using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm}, author={Kwang In Kim and Keechul Jung and Jin Hyung Kim}, journal={IEEE Trans. Pattern Anal. Mach. Intell.}, year={2003}, volume={25}, pages={1631-1639} }