License plate character segmentation using likelihood maximization

A system for determining a license plate layout configuration, the system comprising:

• a training device including a processor for generating at least one model representing a license plate layout configuration, the training device being adapted to:
• segment training images of license plates to extract characters and logos from the training images,
• calculate values corresponding to parameters of the license plate and features of the characters and logos,
• and,
• estimate a likelihood function specified by the features using the values, the likelihood function being adapted to measure deviations between an observed plate and the model;
• a storage device in communication with the training device, the storage device being adapted to store a layout structure and the distributions for each model;
• a segmentation device in communication with the storage device, wherein upon receipt of an observed image including a plate region, the segmentation device is adapted to:
• compare the plate region to the at least one model stored in the storage device;
• and,
• based on the comparison, determine a license plate layout configuration of the observed.

A method for segmenting an observed image of a license plate for determining a layout configuration of the license plate, the method including:

• providing at least one model representing a license plate layout configuration;
• receiving as input an observed image including a plate region;
• producing binary maps of the plate region by applying at least two binary thresholds;
• using the binary maps to determine object connected components relative to background connected components;
• matching the determined black connected components against the at least one model;
• determining if the matching score for the at least one model is below a pre-set threshold;
• and,
• determining if the at least one model is a closest match to the plate region in the observed image.