1 Department of Electronics and Communication Engineering, Government Polytechnic, Hiriyur- 577599, Karnataka, India.
2 Department of Computer Science and Engineering, SIET, Tumkur 572106, Karnataka, India.
Research Article
World Journal of Advanced Research and Reviews, 2019, 03(03), 156-164
Received on 05 October 2019; revised on 15 October 2019; accepted on 23 October 2019
Vehicle recognition in traffic images is a critical component of intelligent transportation systems. This paper explores the use of feature fusion techniques to improve vehicle detection and classification accuracy. Feature fusion combines multiple types of visual features to create a more robust representation of vehicles, leading to better recognition performance even in challenging conditions. We review various feature extraction methods, fusion strategies, and classification approaches that have been developed for vehicle recognition tasks. The integration of complementary features such as color, texture, and shape has shown significant improvements in recognition accuracy compared to single-feature approaches.
Vehicle Recognition; Traffic Image Analysis; Feature Fusion; Deep Learning; Convolutional Neural Networks
Preview Article PDF
Chethana N S and Veena N D. Vehicle Recognition in Traffic Images Using Feature Fusion Techniques. World Journal of Advanced Research and Reviews, 2019, 3(3), 156-164. Article DOI: https://doi.org/10.30574/wjarr.2019.3.3.0153