License plate recognition using SKIPSM

Recognition of license plate images is the topic of this paper. The major issue in this problem is the accurate extraction of the license plate character string from varying backgrounds using processing techniques that are reasonably fast. The images are also characterized by nan-uniform illumination. Recognition of the string is relatively straightforward, if the extraction process has been correctly designed. The authors present three different approaches to extraction and their study revealed that the combination of gray-scale morphology with a log gray-scale transform provided accurate extraction of the string. Recognition studies with 700 images captured during day and night periods indicated an overall acceptance rate of nearly 90% with .7% confusion.