5. A device for automatically extracting a validity period of a driving license, the device comprising a storage device and a processor, wherein the storage device is configured for storing a system for automatically extracting a validity period of a driving license; the processor is configured for executing the system to perform the following operations: receiving an image file of a vehicle driving license; extracting candidate contour regions from within the image file according to a contour extraction rule, and selecting from among the extracted candidate contour regions at least one candidate contour region containing an annual inspection validity period; extracting all character contours from within each selected candidate contour region; acquiring a smallest circumscribed rectangle of each character contour in the selected candidate contour region, and dividing image blocks bound by the acquired smallest circumscribed rectangles one by one into individual single-character blocks; sorting these single-character blocks according to their respective positions in the selected candidate contour region; recognizing a corresponding character of each single-character block; generating a character string representing the annual inspection validity period using the recognized characters based on the sorting; and extracting time data in the character string and taking the time data as the annual inspection validity period of the selected candidate contour region.
5. A device for automatically extracting a validity period of a driving license, the device comprising a storage device and a processor, wherein the storage device is configured for storing a system for automatically extracting a validity period of a driving license; the processor is configured for executing the system to perform the following operations: receiving an image file of a vehicle driving license; extracting candidate contour regions from within the image file according to a contour extraction rule, and selecting from among the extracted candidate contour regions at least one candidate contour region containing an annual inspection validity period; extracting all character contours from within each selected candidate contour region; acquiring a smallest circumscribed rectangle of each character contour in the selected candidate contour region, and dividing image blocks bound by the acquired smallest circumscribed rectangles one by one into individual single-character blocks; sorting these single-character blocks according to their respective positions in the selected candidate contour region; recognizing a corresponding character of each single-character block; generating a character string representing the annual inspection validity period using the recognized characters based on the sorting; and extracting time data in the character string and taking the time data as the annual inspection validity period of the selected candidate contour region. 18. The device of claim 5 , wherein the selecting the at least one candidate contour region comprises; entering the extracted candidate contour regions to a trained first deep convolutional neural network (CNN) model; determining a confidence level of each extracted candidate contour region containing an annual inspection validity period; and choosing the extracted candidate contour region as a candidate contour region containing an annual inspection validity period, when the confidence level of the extracted candidate contour region is greater than a predetermined threshold.