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26 April 2024 |
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Article overview
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End-to-end trainable network for degraded license plate detection via vehicle-plate relation mining | | Song-Lu Chen
; Shu Tian
; Jia-Wei Ma
; Qi Liu
; Chun Yang
; Feng Chen
; Xu-Cheng Yin
; | | Date: |
27 Oct 2020 | | Abstract: | License plate detection is the first and essential step of the license plate
recognition system and is still challenging in real applications, such as
on-road scenarios. In particular, small-sized and oblique license plates,
mainly caused by the distant and mobile camera, are difficult to detect. In
this work, we propose a novel and applicable method for degraded license plate
detection via vehicle-plate relation mining, which localizes the license plate
in a coarse-to-fine scheme. First, we propose to estimate the local region
around the license plate by using the relationships between the vehicle and the
license plate, which can greatly reduce the search area and precisely detect
very small-sized license plates. Second, we propose to predict the
quadrilateral bounding box in the local region by regressing the four corners
of the license plate to robustly detect oblique license plates. Moreover, the
whole network can be trained in an end-to-end manner. Extensive experiments
verify the effectiveness of our proposed method for small-sized and oblique
license plates. Codes are available at
this https URL. | | Source: | arXiv, 2010.14266 | | Services: | Forum | Review | PDF | Favorites | |
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