Threshold selection and identification of character regions from complex scene images - Li, Li (2010)
In this research work, a comprehensive algorithm for alphanumeric character detection in general complex scene images is proposed, and specifically applied to car licence-number plate. Recently a number of papers dealing with this problem have been published. They can be broadly divided into two major approaches, i.e., edge-based approach in which the number-plate location is first detected, and grey-level-feature-based approach in which the character candidates are directly detected. These approaches usually need to make some assumptions or to put some constraints on the images to limit their searching work and to improve the success rate. In this thesis, we study the generalisations of the second approach by directly detect the alphanumeric characters at any location in the complex scene image with minimum image constraints.