License plate detection and recognition system

A computing apparatus, the computing apparatus comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, configure the apparatus to perform operations comprising:
• receiving training data comprising images of license plates;
• preparing ground truth data from the training data based on predefined parameters;
• training a first machine learning algorithm based on the ground truth data to generate a license plate detection model, the license plate detection model configured to detect one or more regions in the images, the one or more regions containing a candidate for a license plate, and to generate a bounding box for each license plate;
• training a second machine learning algorithm based on the ground truth data and the license plate detection model to generate a license plate recognition model, the license plate recognition model configured to generate a sequence of alphanumeric characters in the bounding box with a level of recognition confidence for the sequence;
• receiving an input image;
• determining a bounding box corresponding to an image of each candidate license plate in the input image by applying the license plate detection model to the input image, the bounding box indicating a license plate type and a corresponding confidence level;
• and
• generating an array of license plate information comprising an image of a license plate from the input image, a corresponding string identifier, corresponding bounding box coordinates, and a corresponding confidence level.

A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to perform operations comprising:

• receiving training data comprising images of license plates;
• preparing ground truth data from the training data based on predefined parameters;
• training a first machine learning algorithm based on the ground truth data to generate a license plate detection model, the license plate detection model configured to detect one or more regions in the images, the one or more regions containing a candidate for a license plate, and to generate a bounding box for each license plate;
• training a second machine learning algorithm based on the ground truth data and the license plate detection model to generate a license plate recognition model, the license plate recognition model configured to generate a sequence of alphanumeric characters in the bounding box with a level of recognition confidence for the sequence;
• receiving an input image;
• determining a bounding box corresponding to an image of each candidate license plate in the input image by applying the license plate detection model to the input image, the bounding box indicating a license plate type and a corresponding confidence level;
• and
• generating an array of license plate information comprising an image of a license plate from the input image, a corresponding string identifier, corresponding bounding box coordinates, and a corresponding confidence level.