Extraction of Text under Complex Background Using Wavelet Transform and Support Vector Machine
- Resource Type
- Conference
- Authors
- Hongxing Sun; Nannan Zhao; Xinhe Xu
- Source
- 2006 International Conference on Mechatronics and Automation Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on. :1493-1497 Jun, 2006
- Subject
- Robotics and Control Systems
Components, Circuits, Devices and Systems
Computing and Processing
Wavelet transforms
Support vector machines
Support vector machine classification
Discrete wavelet transforms
Data mining
Digital images
Robotics and automation
Artificial intelligence
Intelligent robots
Acceleration
text detection
texture analysis
wavelet transform
machine learning
SVM
- Language
- ISSN
- 2152-7431
2152-744X
A method based on wavelet transform and support vector machine (SVM) for detecting text under complex background is proposed. First, the image is decomposed by wavelet, and then the texture characteristic of text is extracted by using SVM on low-frequency approximate sub-space and high-frequency energy sub-space. Combining wavelet transform and SVM not only reduces the number of input training samples but also accelerates the speed of SVM for learning and classification. This method utilizes the characteristic that SVM is suited to high-dimension space work and improves the efficiency of extracting text. Experimental results show that the current proposed method can correctly and effectively locate text region in the digital image.