Number recognition using inductive learning on spiral architecture

In this paper, a number recognition algorithm on Spiral Architecture is proposed. This algorithm employs RULES-3 inductive learning method and template matching technique. The algorithm starts from a collection of samples of numbers or letters used in number plates. Edge maps of the samples are then detected based on Spiral Architecture. A set of rules are extracted using these samples by RULES-3. The rules describe the frequencies of 9 different edge masks appearing in the samples. Each mask is a cluster of 7 hexagonal pixels. In order to recognize a number plate, all characters (digits or letters) are tested one by one using the extracted rules. The number recognition is achieved by the frequencies of the 9 masks