Object-Text Detection and Recognition System

Pervez Shoaib Ilyasi, Gautam Gupta, M. S. Sai, K. Saatwik, B. S. Kumar, Dinesh Vij
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Abstract

The object recognition system based on deep learning has been applied in different domains, e.g. in the Intelligent transportation system, Autonomous driving system, etc. Along with object detection, in numerous scenes, text detection and recognition have conjointly brought abundant attention and analysis application.Real-time object detection and dimensioning as well as text recognition are important topics for many branches of the industry today.The projected system consists of object – text, detection and recognition module, and a dimension measuring module. This system offers an improved method of classifying objects and calculating their measures in real-time from video sequences. The proposed system uses OpenCV libraries, which comprise erosion algorithms, canny edge detection, dilation, and contour detection. To accomplish the task of the text recognition Tesseract OCR engine is employed.
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对象文本检测与识别系统
基于深度学习的目标识别系统在智能交通系统、自动驾驶系统等领域得到了广泛的应用。与目标检测一样,在众多的场景中,文本检测和识别也得到了广泛的关注和分析应用。实时对象检测和标注以及文本识别是当今许多行业分支的重要主题。投影系统由目标文本、检测识别模块和尺寸测量模块组成。该系统提供了一种改进的从视频序列中对目标进行实时分类并计算其度量的方法。该系统采用OpenCV库,包括侵蚀算法、边缘检测、扩张和轮廓检测。为了完成文本识别的任务,采用了Tesseract OCR引擎。
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