You can view the full text of this article for free using the link below.

Title: An automated vision-based algorithm for out of context detection in images

Authors: R. Karthika; Latha Parameswaran

Addresses: Department of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India ' Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India

Abstract: Vehicular traffic on highways is a major concern relating to safety and security. Violation of traffic rules results in fatal incidents to a very large extent. In this work, an attempt has been made to detect violation of traffic rules namely vehicles in no parking and no stopping zones. Dataset consisting of cars in these zones has been used for experimentation. The proposed algorithm used histograms of oriented gradient (HOG) and Adaboost cascaded classifier for training. The traffic signs have been identified using Hough transform, Circlet transform and colour analysis. Experimental results are promising with an accuracy in the range of 90-97% with recognising no parking and no stopping sign.

Keywords: traffic sign; car detection: histograms of oriented gradient; HOG; circlet transform; Adaboost.

DOI: 10.1504/IJSISE.2018.090601

International Journal of Signal and Imaging Systems Engineering, 2018 Vol.11 No.1, pp.1 - 8

Accepted: 21 Aug 2017
Published online: 23 Mar 2018 *

Full-text access for editors Full-text access for subscribers Free access Comment on this article