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A low complexity method for detection of text area in natural images

机译:一种低复杂度的自然图像文本区域检测方法

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We propose a low complexity method for segmentation of text regions in natural images. This algorithm is designed for mobile applications (e.g. unmanned or hand-held devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, character set or the camera angle. However, the text is assumed to be located on a piecewise homogeneous background with a contrasting color. We have deployed our method on a Nokia N800 Internet tablet as part of a system for automatic detection and translation of outdoor signs. Our experiments show that the 0.3 megapixel images taken by the phone camera can be accurately segmented within the device in a fraction of a second.
机译:我们提出了一种用于自然图像中文本区域分割的低复杂度方法。该算法设计用于计算和能源有限的移动应用(例如,无人驾驶或手持设备)。对于文本大小,字体,语言,字符集或摄像机角度,没有事先假设。但是,假定文本位于具有对比色的分段均质背景上。我们已将我们的方法部署在诺基亚N800互联网平板电脑上,作为自动检测和翻译室外标志的系统的一部分。我们的实验表明,通过电话摄像头拍摄的0.3百万像素图像可以在不到一秒的时间内在设备内准确分割。

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