Joint image enhancement and localization framework for vehicle model recognition in the presence of non-uniform lighting conditions

Landry Kezebou; Victor Oludare; Karen Panetta; Sos Agaian

doi:10.1117/12.2586036

12 April 2021 Joint image enhancement and localization framework for vehicle model recognition in the presence of non-uniform lighting conditions

Landry Kezebou, Victor Oludare, Karen Panetta, Sos Agaian

Author Affiliations +

Proceedings Volume 11734, Multimodal Image Exploitation and Learning 2021; 117340Q (2021) https://doi.org/10.1117/12.2586036
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Conference Poster

Abstract

Recognizing the model of a vehicle in natural scene images is an important and challenging task for real-life applications. Current methods perform well under controlled conditions, such as frontal and horizontal view-angles or under optimal lighting conditions. Nevertheless, their performance decreases significantly in an unconstrained environment, that may include extreme darkness or over illuminated conditions. Other challenges to recognition systems include input images displaying very low visual quality or considerably low exposure levels. This paper strives to improve vehicle model recognition accuracy in dark scenes by using a deep neural network model. To boost the recognition performance of vehicle models, the approach performs joint enhancement and localization of vehicles for non-uniform-lighting conditions. Experimental results on several public datasets demonstrate the generality and robustness of our framework. It improves vehicle detection rate under poor lighting conditions, localizes objects of interest, and yields better vehicle model recognition accuracy on low-quality input image data.

Conference Presentation

Citation Download Citation

Landry Kezebou, Victor Oludare, Karen Panetta, and Sos Agaian "Joint image enhancement and localization framework for vehicle model recognition in the presence of non-uniform lighting conditions", Proc. SPIE 11734, Multimodal Image Exploitation and Learning 2021, 117340Q (12 April 2021); https://doi.org/10.1117/12.2586036

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