文章基本信息

标题：Text Extraction from Natural Scene Images using OpenCV and CNN
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作者：Vaibhav Goel ; Vaibhav Kumar ; Amandeep Singh Jaggi 等
期刊名称：International Journal of Information Technology and Computer Science
印刷版ISSN：2074-9007
电子版ISSN：2074-9015
出版年度：2019
卷号：11
期号：9
页码：48-54
DOI：10.5815/ijitcs.2019.09.06
出版社：MECS Publisher
摘要：The influence of exponentially increasing camera-embedded smartphones all around the world has magnified the importance of computer vision tasks, and gives rise to a vast number of opportunities in the field. One of the major research areas in this field is the extraction of text embedded in natural scene images. Natural scene images are the images taken from a camera, where the background is random, and the variety of colors used in the image may be diverse. When text is present in such type of images, it is usually difficult for a machine to detect and extract this text due to a number of parameters. This paper presents a technique that uses a combination of the Open Source Computer Vision Library (OpenCV) and the Convolutional Neural Networks (CNN), to extract English text from images efficiently. The CNN model is based on a two-stage pipeline that uses a single neural network to directly detect the characters in the scene images. It eliminates the unnecessary intermediate steps that are present in the previous approaches to this task making them slower and inaccurate, thereby improving the time complexity and the performance of the algorithm.
关键词：Text Extraction;Deep Learning;OpenCV;natural scene images;CNN;Optical Character Recognition