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Text Detection and Recognition Using Camera Based Images

机译:基于相机的图像的文本检测和识别

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摘要

The increase in availability of high performance, low-priced, portable digital imaging devices has created an opportunity for supplementing traditional scanning for document image acquisition. Cameras attached to cellular phones, wearable computers, and standalone image or video devices are highly mobile and easy to use; they can capture images making them much more versatile than desktop scanners. Should gain solutions to the analysis of documents captured with such devices become available, there will clearly be a demand in many domains. Images captured from images can suffer from low resolution, perspective distortion, and blur, as well as a complex layout and interaction of the content and background.In this paper, we propose an efficient text detection method based on Maximally Stable Exterme Region (MSER) detector, saying that how to detect regions containing text in an image. It is a common task performed on unstructured scenes, for example when capturing video from a moving vehicle for the purpose of alerting a driver about a road sign . Segmenting out the text from a clutterd scene greatly helps with additional tasks such as optical charater recognition (OCR). The efficiency of any service or product, especially those related to medical field depends upon its applicability. The applicability for any service or products can b achieved by applying thr basic principles of Software Engineering.
机译:高性能,低价,便携式数字成像设备的可用性增加已经为补充传统扫描的文档图像采集创造了机会。连接到蜂窝电话,可穿戴计算机和独立图像或视频设备的摄像机非常移动且易于使用;他们可以捕获图像使它们比桌面扫描仪更容易。应该增益解决因这些设备捕获的文件的分析而可用,在许多领域都会显然有所要求。图像捕获的图像可能会遭受低分辨率,透视失真和模糊,以及内容和背景的复杂布局和交互。在本文中,我们提出了一种基于最大稳定的外部区域(MSER)的有效文本检测方法探测器,说如何检测图像中包含文本的区域。它是在非结构化场景上执行的常见任务,例如,当捕获来自移动车辆的视频以提醒驾驶员关于道路标志的目的。从Clutterd场景中分割文本非常有助于使用诸如光学校正(OCR)等附加任务。任何服务或产品的效率,特别是与医疗领域相关的效率取决于其适用性。通过应用软件工程的基本原理来实现任何服务或产品的适用性。

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