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首页> 外文期刊>Journal of visual communication & image representation >Novel video stabilization for real-time optical character recognition applications
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Novel video stabilization for real-time optical character recognition applications

机译：用于实时光学字符识别应用的新型视频稳定

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This paper presents a novel video stabilization algorithm for real-time optical character recognition (OCR) applications. The proposed method generates output frames in order to stabilize the position of a target word that will be recognized by the OCR application. Unlike in conventional algorithms, in the proposed algorithm, a causal low pass filter is not applied to the trajectory of the target word for reducing the high frequency component of camera motion. The proposed algorithm directly calculates the stable position of the word using two forces: the force used to pull the target word to the center of an output frame and a back force used to return the center of an output frame to the center of an input frame. Hence, the proposed algorithm significantly minimizes the time take to respond to sudden camera movement. Although the proposed method may not outperform state-of-the-art video stabilization in terms of video stability, the proposed technique is much more appropriate for real-time OCR applications than the conventional techniques in terms of accuracy, computational cost, processing delay, and the time taken to respond to sudden camera movement. Simulation results prove the superiority of the proposed method over conventional techniques for real-time OCR applications. (C) 2017 Elsevier Inc. All rights reserved.
机译：本文提出了一种用于实时光学字符识别（OCR）应用的新型视频稳定算法。所提出的方法生成输出帧，以便稳定将由OCR应用程序识别的目标单词的位置。与传统算法不同，在所提出的算法中，因果低通滤波器未应用于目标单词的轨迹，以减少摄像机运动的高频分量。所提出的算法使用两个力直接计算单词的稳定位置：用于将目标单词拉到输出帧中心的力和用于将输出帧中心返回到输入帧中心的反力。因此，所提出的算法极大地减少了响应相机突然运动所需的时间。尽管就视频稳定性而言，所提出的方法可能无法胜过最新的视频稳定性，但就准确性，计算成本，处理延迟，以及响应相机突然移动所需的时间。仿真结果证明了该方法在实时OCR应用中优于传统技术的优越性。 （C）2017 Elsevier Inc.保留所有权利。

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