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http://dx.doi.org/10.5391/JKIIS.2007.17.7.930

Control of Time-varying and Nonstationary Stochastic Systems using a Neural Network Controller and Dynamic Bayesian Network Modeling  

Cho, Hyun-Cheol (동아대학교 전기공학과)
Lee, Jin-Woo (동아대학교 전기공학과)
Lee, Young-Jin (한국폴리텍 항공대학 항공전기과)
Lee, Kwon-Soon (동아대학교 전기공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.17, no.7, 2007 , pp. 930-938 More about this Journal
Abstract
Captions which appear in images include information that relates to the images. In order to obtain the information carried by captions, the methods for text extraction from images have been developed. However, most existing methods can be applied to captions with fixed height of stroke's width. We propose a method which can be applied to various caption size. Our method is based on connected components. And then the edge pixels are detected and grouped into connected components. We analyze the properties of connected components and build a neural network which discriminates connected components which include captions from ones which do not. Experimental data is collected from broadcast programs such as news, documentaries, and show programs which include various height caption. Experimental result is evaluated by two criteria : recall and precision. Recall is the ratio of the identified captions in all the captions in images and the precision is the ratio of the captions in the objects identified as captions. The experiment shows that the proposed method can efficiently extract captions various in size.
Keywords
Neural network control; Dynamic Bayesian networks; Stochastic process; Nonstationary statistics; Time-varying dynamics;
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