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Research Article | Open Access |

A Novel Approach for On-road Vehicle Detection and Tracking

Author 1: Ilyas EL JAAFARI Author 2: Mohamed EL ANSARI Author 3: Lahcen KOUTTI Author 4: Ayoub ELLAHYANI Author 5: Said CHARFI
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 1 · Published 2016 · Cited by 15

DOI: https://doi.org/10.14569/IJACSA.2016.070181

Abstract

On the basis of a necessary development of the road safety, vision-based vehicle detection techniques have gained an important amount of attention. This work presents a novel vehicle detection and tracking approach, and structured based on a vehicle detection process starting from, images or video data acquired from sensors installed on board of the vehicle, to vehicle detection and tracking. The features of the vehicle are extracted by the proposed GIST image processing algorithm, and recognized by the state-of-art Support Vectors Machine classifier. The tracking process was performed based on edge features matching approach. The Kalman filter was used to correct the measurements. Extensive experiments were carried out on real image data validate that it is promising to employ the proposed approach for on road vehicle detection and tracking.

Keywords

How to Cite this Article

JAAFARI, I. E., ANSARI, M. E., KOUTTI, L., ELLAHYANI, A., & CHARFI, S. (2016). A Novel Approach for On-road Vehicle Detection and Tracking. International Journal of Advanced Computer Science and Applications, 7(1). https://doi.org/10.14569/IJACSA.2016.070181

JAAFARI, Ilyas EL, et al.. "A Novel Approach for On-road Vehicle Detection and Tracking." International Journal of Advanced Computer Science and Applications, vol. 7, no. 1, 2016, https://doi.org/10.14569/IJACSA.2016.070181.

@article{JAAFARI2016,
  title     = {A Novel Approach for On-road Vehicle Detection and Tracking},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {1},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ilyas EL JAAFARI and Mohamed EL ANSARI and Lahcen KOUTTI and Ayoub ELLAHYANI and Said CHARFI},
  doi       = {10.14569/IJACSA.2016.070181},
  url       = {https://doi.org/10.14569/IJACSA.2016.070181}
}

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