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首页> 外文期刊>International Journal of Image and Graphics >A Light Weight Text Extraction Technique for Hand-Held Device
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A Light Weight Text Extraction Technique for Hand-Held Device

机译:手持设备的轻量文本提取技术

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Automated systems for understanding display boards are finding many applications useful in guiding tourists, assisting visually challenged and also in providing location aware information. Such systems require an automated method to detect and extract text prior to further image analysis. In this paper, a new approach that uses zonewise profile features to identify and segment text regions from low resolution images of display boards captured from mobile phone cameras is presented. The method computes zonewise profile features on every 40 × 40 pixel image block and identifies potential text blocks using newly defined discriminant functions. Further, a merging algorithm is used to merge text blocks to obtain text regions. The method is implemented using the android software development kit and experimented on Sony X-PeriaTM Z C6603/C6602 mobile. The proposed methodology is evaluated on 3240 low resolution images of display boards captured from 2 and/or 5 mega pixel cameras on mobile phones at various pixel sizes 240×320, 480×640 and 960×1280 and reports an average processing time of 13 s and detection rate of 95.5%. The proposed method is found to be robust and insensitive to the variations in size and style of font, thickness and spacing between characters.
机译:用于理解显示板的自动化系统发现了许多有用的应用程序,它们可以引导游客,帮助视觉障碍者以及提供位置感知信息。这样的系统需要在进一步的图像分析之前检测和提取文本的自动化方法。在本文中,提出了一种新的方法,该方法使用区域性配置文件功能来识别和分割从手机相机捕获的显示板的低分辨率图像中的文本区域。该方法在每个40×40像素的图像块上计算区域轮廓特征,并使用新定义的判别函数识别潜在的文本块。此外,合并算法用于合并文本块以获得文本区域。该方法使用android软件开发套件实现,并在Sony X-PeriaTM Z C6603 / C6602移动版上进行了实验。在从2个和/或5个百万像素摄像机的手机上以各种像素尺寸240×320、480×640和960×1280捕获的3240个低分辨率显示板图像上评估了所提出的方法,并报告了平均13 s的处理时间检出率为95.5%。发现所提出的方法是健壮的并且对字体的大小和样式,字符的粗细和间距的变化不敏感。

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