A traffic sign recognition method under complex illumination conditions

نویسندگان

چکیده

Environment awareness technology is one of the most critical technologies for autonomous vehicles, and traffic sign recognition an important branch environment system, which has research significance ensuring safety. To solve problems easy omission inaccurate positioning detection under complex illumination conditions, there are two main innovations in this paper: firstly, adaptive image enhancement algorithm was proposed to improve quality conditions; Secondly, a novel lightweight attention block named Feature difference (FD) model detect recognize signs. Unlike state-of-the-art models, utilizes between feature maps generate mask. In work, single-stage target SSD selected as basic network, backbone network set ResNet VGG respectively FD module added. A large number experiments were carried out evaluate optimization effect module. The following conclusions can be drawn: algorithms provide better samples; integrated into CNNs just by adding some shortcut connections, does not introduce any additional parameters layers; average accuracy with 1.80% higher recall rate 1.51% than that without module, no great influence on running speed. dark detection; slightly other modules including BAM, CBAM SE; used convolutional operation features, could help find layers have little pruning.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2023

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2023.3266825