Vijeta Khare

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In this paper, we present a simple and novel technique for classification of multiple channel electrooculogram signals (EOG). In particular, a viable real-time EOG signal classifier is proposed. The classifier is based on deterministic finite automata (DFA). The system is capable of classifying sixteen different EOG signals and can be used universally for(More)
Text detection in arbitrarily-oriented multi-lingual video is an emerging area of research because it plays a vital role for developing real-time indexing and retrieval systems. In this paper, we propose to explore moments for identifying text candidates. We introduce a novel idea for determining automatic windows to extract moments for tackling multi-font(More)
Detection of moving text of different orientations in video is challenging because of low resolution and complex background of video. In this paper, we propose a method based on motion vectors to identify the moving blocks which have linear and constant velocity. For each block, we compute moments and use k-means clustering algorithm to extract text(More)
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