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A Low Complexity Sign Detection and Text Localization Method for Mobile Applications

机译:用于移动应用程序的低复杂度符号检测和文本本地化方法

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摘要

We propose a low complexity method for sign detection and text localization in natural images. This method is designed for mobile applications (e.g., unmanned or handheld devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, or character set. However, the text is assumed to be located on a homogeneous background using a contrasting color. We have deployed our method on a Nokia N800 cellular phone as part of a system for automatic detection and translation of outdoor signs. This handheld device is equipped with a 0.3-megapixel camera capable of acquiring images of outdoor signs that typically contain enough details for the sign to be readable by a human viewer. Our experiments show that the text of these images can be accurately localized 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的符号检测和文本定位的低复杂度方法。该方法设计用于计算和能源有限的移动应用程序(例如,无人驾驶或手持设备)。对于文本大小,字体,语言或字符集,没有事先假设。但是,使用对比色假定文本位于均匀的背景上。我们已在诺基亚N800蜂窝电话上部署了我们的方法,作为自动检测和翻译室外标志的系统的一部分。该手持设备配备有0.3百万像素的摄像头,能够获取室外招牌的图像,这些图像通常包含足够的细节,以使观众可以阅读。我们的实验表明,这些图像的文本可以在几分之一秒内准确定位在设备中。

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