Abstract
We analyze some spatial frequency-based features used for text region detection in natural scene images, and redefine the DCT-based feature. We employ Fisher's discriminant analysis to improve the DCT-based feature and to achieve higher accuracy. An unsupervised thresholding method for discriminating text and non-text regions is introduced and tested as well. Experimental results show that a wide high frequency band, covering some lower-middle frequency components, is generally more suitable for scene text detection despite the original definition of the DCT-based feature.
Original language | English |
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Pages (from-to) | 1-8 |
Number of pages | 8 |
Journal | International Journal on Document Analysis and Recognition |
Volume | 11 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2008 Mar 13 |
Keywords
- Discrete cosine transform
- Fisher's discriminant analysis
- Scene text
- Text region detection
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications