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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Nguyen, Vinh Dinh
FPT University, Can Tho Campus, Vietnam
Computer Science & IT Electrical & Electronics Engineering

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Robust Stereo Matching for Driver Assistance Systems Under Adverse Driving Conditions Nguyen, Vinh Dinh; Tran, Nhan Huu
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 13, No 4: December 2025
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v13i4.6686

Abstract

Deep stereo networks perform effectively when both training and testing data come from the same domain. However, their accuracy tends to drop significantly in efficiency-focused target scenarios due to domain shifts between training and testing datasets. These shifts often arise from differences in factors such as color, lighting, contrast, and texture. Additionally, the architecture of deep networks generally results in processing times that are unsuitable for real-time applications. To address these issues, this paper proposes a lightweight and robust stereo matching approach tailored for diverse driving environments. It leverages attention mechanisms for feature extraction and uses evolutionary algorithms for optimizing parameters. The method outperforms existing deep learning and traditional stereo matching techniques in terms of both processing speed and the percentage of bad pixels, as demonstrated on three challenging outdoor datasets: KITTI, HCI, and Driving Stereo. These results indicate that the proposed solution is highly effective for real-world applications where both precision and flexibility are essential.
Co-Authors Tran, Nhan Huu