Detecting Character in Video Frames for Traffic Vehicle

International Journal of Computer Science and Engineering

© 2017 by SSRG - IJCSE Journal

Volume 4 Issue 9

Year of Publication : 2017

Authors : P. Mahalakshmi, T. Manigandan, D. Chitra

10.14445/23488387/IJCSE-V4I9P102

How to Cite?

P. Mahalakshmi, T. Manigandan, D. Chitra, "Detecting Character in Video Frames for Traffic Vehicle," SSRG International Journal of Computer Science and Engineering , vol. 4,  no. 9, pp. 9-13, 2017. Crossref, https://doi.org/10.14445/23488387/IJCSE-V4I9P102

Abstract:

Reading text from video frames is a challenging problem that has received a significant amount of attention. The two key components of most systems are (i) text detection from images and (ii) character recognition and many recent methods have been proposed to design better feature representations and models for both. Detection of text and identification of characters in scene images is a challenging visual recognition problem. As in much of computer vision the challenges posed by the complexity of these images have been combated with hand designed features [1], [2], [3] and models that incorporate various pieces of high-level prior knowledge [4], [5]. The produce results from a system that attempts to learn the necessary features directly from the data as an alternative to using purpose-built text-specific features or models. Detecting text regions in natural scene images has become an important area due to its varies applications. Scene text detection from video as well as natural scene images is challenging due to the variations in background, contrast, text type, font type, font size, etc. Besides arbitrary orientations of texts with multi-scripts add more complexity to the problem. Text Information Extraction (TIE) System involves detecting text regions in a given image, localizing it, extracting the text part and recognizing text using OCR. The extracted features are used by the trained SVM classifier to detect the text regions. After detecting text regions characters are extracted and finally displayed. Text in camera captured images contains important and useful information. Text in images can be used for identification indexing and retrieval. Detection and localization of text from camera captured images is still a challenging task due to high variability of text appearance detected text regions are merged and localized.

Keywords:

Text detection, Character Recongnition, Computer Vision, Text Information Extraction, SVM, OCR.

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