5. The method of claim 1 further comprising: splitting a single, wide initial character boundary into two by placing a boundary at a minimum histogram value in a region near a center of said wide initial character boundary; and replacing a large gap caused by omission of a special character with a missing image data.
1. A license plate character segmentation method, said method comprising: determining an initial character boundary of a vehicle image utilizing a midpoint of a segment along a vertical projection histogram in order to partition said initial character boundary from said vehicle image; classifying said initial character boundary as a valid character boundary or a suspect character boundary; analyzing said suspect character boundary and enabling robust performance over a plurality of state logos, fonts, and character spacing; receiving a character image and a label and identifying said character image utilizing said label as a likely character or not; creating a copy of an input character label array as outlabel and initializing all values of said outlabel to zero; setting each element in said outlabel to one for a character identified as a non-character that is touching a boundary until a valid character is encountered; assigning said outlabel element to two for each non-character surrounded by said valid character; setting said outlabel element to three for each set of at least two non-characters surrounded by said valid character and combining at least two images and copying to a first location for each set of element in said outlabel set to three and also set outlabel for second location back to one; and normalizing and passing said suspect character boundary to an optical character recognition subsystem for decoding and generating a confidence quote for each suspect character boundary of said vehicle image analyzed and thereafter modifying each suspect character boundary decoded based on a set of confidence thresholds.