Title: Automatic text detection in video frames based on bootstrap artificial neural network and CED
Authors: Hao, Yan
Yi, Zhang
Zeng-guang, Hou
Min, Tan
Citation: Journal of WSCG. 2003, vol. 11, no. 1-3.
Issue Date: 2003
Publisher: UNION Agency – Science Press
Document type: článek
URI: http://wscg.zcu.cz/wscg2003/Papers_2003/D31.pdf
ISSN: 1213-6972
Keywords: detekce textu;umělá neuronová síť;video snímky
Keywords in different language: text detection;artificial neural network;video frames
Abstract: In this paper, one novel approach for text detection in video frames, which is based on bootstrap artificial neural network (BANN) and CED operator, is proposed. This method first uses a new color image edge operator (CED) to segment the image and achieve the elementary candidate text block. And then the neural network is introduced into the further classification of the text blocks and the non-text blocks in video frames. The idea of bootstrap is introduced into the training of the ANN, thus improving the effectiveness of the neural network greatly. Experiments results proved that this method is effective.
Rights: © UNION Agency – Science Press
Appears in Collections:Volume 11, number 1-3 (2003)

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/1666

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