License plate detection method and device

A terminal, comprising:

• a housing, a processor, a memory, a circuit board and a power supply circuit, wherein, the circuit board is arranged within a space enclosed by the housing;
• the processor and memory are disposed on the circuit board;
• the power supply circuit is configured for supplying power to circuits and devices of the terminal;
• the memory is configured for storing executable program instructions;
• and the processor is configured for executing the executable program instructions stored in the memory to perform:
• obtaining, according to pixel values of pixels in an image to be detected, a candidate license plate area M1 in the image to be detected;
• calculating an aspect ratio of the candidate license plate area M1 and determining whether the aspect ratio is greater than a first predefined threshold;
• if the aspect ratio is greater than the first predefined threshold, determining a new candidate license plate area M2 from the candidate license plate area M1 according to a predefined machine learning-based regression algorithm, wherein the candidate license plate area M2 is an area whose aspect ratio is no greater than the first predefined threshold;
• determining, according to a first predefined classification model, whether the candidate license plate area M2 is a license plate area, wherein, the first predefined classification model is a classification model obtained by learning sample license plate areas through a machine learning algorithm, and wherein, in constructing of the first classification model, a lame amount of sample license plate areas previously found are learned through the machine learning algorithm so as to obtain a classification model, by means of which an area of the candidate license plate area is classified into a license plate area and non-license plate area;
• if the candidate license plate area M2 is a license plate area, determining the candidate license plate area M2 as a license plate area, and generating a detection result based on the candidate license plate area M2,
• wherein, determining a new candidate license plate area M2 from the candidate license plate area M1 according to a predefined machine learning-based regression algorithm comprises:
• determining a position of a suspected character string in the candidate license plate area M1;
• determining, through the predefined machine learning-based regression algorithm, a new boundary of the candidate license plate area according to the determined position;
• and
• obtaining the candidate license plate area M2 according to the new boundary.