Comparative Study on Text Detection and Recognition from Traffic Image

Authors

  • Asit Kumar M.Tech Scholar Department of Electronic & Communication OCT, Bhopal
  • Sumit Kumar Assistant Professor Department of Electronic & Communication OCT, Bhopal

DOI:

https://doi.org/10.24113/ijoscience.v2i9.114

Keywords:

Scene structure, text detection, Maximally Stable Extremal Regions (MSER), traffic text sign recognition.

Abstract

Text plays an significant role in day-to-day life because of its dissimilarities in text size, font, style, orientation and alignment as well as composite background and rich information, as a consequence automatic text detection in natural scenes has several attractive applications. Though, detecting and recognizing such text is all the time a challenging issue. Several text extraction techniques grounded on edge detection, connected component analysis, morphological operators, wavelet transform, texture features, neural network etc. have been established. This paper contributes comparative analysis of different technique which provides efficient performance.

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Published

12/30/2016

How to Cite

Kumar, A., & Kumar, S. (2016). Comparative Study on Text Detection and Recognition from Traffic Image. SMART MOVES JOURNAL IJOSCIENCE, 2(9). https://doi.org/10.24113/ijoscience.v2i9.114