End-to-end license plate recognition method and device based on lightweight network
A license plate recognition and network-side technology, which is applied in the field of end-to-end license plate recognition methods and devices based on lightweight networks, can solve the problems of low efficiency and accuracy of license plate number recognition
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Embodiment 1
[0054] figure 1 A schematic flowchart of an embodiment of the light-weight network-based end-to-end license plate recognition method of the present invention, figure 2 It is a schematic diagram of the organizational structure of a lightweight license plate recognition network model according to an embodiment of the present invention.
[0055] like Figure 1 to Figure 2 As shown, this embodiment provides an end-to-end license plate recognition method based on a lightweight network, the lightweight network is a lightweight license plate recognition network model, and the lightweight license plate recognition network model includes a feature extraction network, a differentiated character classification network and license plate number encoding / decoding module; the method may include:
[0056] Step 101, acquiring a license plate image.
[0057] The acquisition of the license plate image may be captured by a surveillance camera located at an intersection, a bayonet, a parking l...
Embodiment 2
[0092] see figure 2 and Figure 7 As shown, the device of this embodiment can include: a lightweight license plate recognition network model, including a feature extraction network, a differentiated character classification network, and a license plate number compilation / decoding module; the functions realized by the license plate number compilation / decoding module can be programmed The method is solidified in the differentiated classification network.
[0093] Wherein, the feature extraction network is used to input the license plate image into the feature extraction network, perform shallow-level processing on the license plate image, and extract the shallow-level texture features of the license plate image;
[0094] performing deep-level processing on the shallow-level texture features, and extracting deep-level features of the license plate image;
[0095] Obtaining advanced semantic features based on the deep-level features to obtain multiple feature maps; the size spe...
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