Digital Object Identifier (DOI) 10.1007/s00530-004-0157-0 Multimedia Systems Video text detection and segmentation for optical character recognition
Digital Object Identifier (DOI) 10.1007/s00530-004-0157-0 Multimedia Systems Video text detection and segmentation for optical character recognition
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DOI：
10.1007/s00530-004-0157-0
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发表时间：
2005-03
影响因子：
3.9
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中科院分区：
文献类型：
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在本文中，我们提出的方法来检测和分割视频中的文本。所提出的视频文本检测技术是能够自适应地适用于不同形式的视频帧通过分类的背景复杂性适当的运营商。对边缘密度高的图像采用了有效的算子，如重复移位算子。同时，使用文本增强技术来突出低对比度图像的文本区域。然后采用由粗到细的投影技术从视频帧中提取文本行。实验结果表明，本文提出的文本检测方法在检测率和误报率方面上级基于机器学习（如SVM和神经网络）、基于多分辨率和基于DCT的方法。在文本检测的基础上，提出了一种基于自适应阈值的文本分割方法。然后使用商业OCR包来识别分割的前景文本。在实验中取得了令人满意的字符识别率。
In this paper, we present approaches to detecting and segmenting text in videos. The proposed video-text-detection technique is capable of adaptively applying appropriate operators for video frames of different modalities by classifying the background complexities. Effective operators such as the repeated shifting operations are applied for the noise removal of images with high edge density. Meanwhile, a text-enhancement technique is used to highlight the text regions of low-contrast images. A coarse-to-fine projection technique is then employed to extract text lines from video frames. Experimental results indicate that the proposed text-detection approach is superior to the machine-learning-based (such as SVM and neural network), multiresolution-based, and DCT-based approaches in terms of detection and false-alarm rates. Besides text detection, a technique for text segmentation is also proposed based on adaptive thresholding. A commercial OCR package is then used to recognize the segmented foreground text. A satisfactory character-recognition rate is reported in our experiments.