Vision based Vehicle Detection with Fog Removal Algorithm
Divya Sahgal1, A. Ramesh2
1Divya Sahgal, Department of Computer Science, Amity University, Gurugram (Haryana), India.
2Dr. A. Ramesh, Department of Management Studies, IIT Roorkee, India.
Manuscript received on 28 March 2019 | Revised Manuscript received on 07 April 2019 | Manuscript Published on 11 April 2019 | PP: 174-178 | Volume-8 Issue-4C, April 2019 | Retrieval Number: D24400484C19/19©BEIESP
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Abstract: The present study proposes a vision-based technique for Vehicle Detection in foggy weather condition. The methodology used in this approach is based on image processing. MATLAB is used to execute algorithm with image processing toolbox. Gabor wavelets technique has been used to extract features from images. This paper aims to improve the visibility of degraded images due to foggy weather condition, which can be used for the vehicle detection at traffic intersection for traffic control and management. It proposes an improved technique with fog removal option for the restoration of low-density image, which is damaged by reducing the contrast of the picture due to foggy weather. The proposed methodology combines the CLAHE method and adaptive gamma modification to achieve the purpose of this research work. This algorithm works effectively in different weather situations to ensure efficient vehicle detection at the traffic intersection.
Keywords: MATLAB, Vision-Based, Intelligent Transportation Systems, Applications, Vehicle-to-vehicle, Vehicle Detection, Fog Removal, Image Processing.
Scope of the Article: VLSI Algorithms