A robust doorplate recognition system

In real applications, captured doorplate images often contain unexpected noise from irregular illumination conditions, various imaging angles, different imaging distances, etc. In this paper, a robust doorplate recognition system is presented. First, an efficient method based on Sobel operator, region splitting and merging is applied to extract doorplate. Then, according to the doorplate shape and the character position in the doorplate, the character region is determined. If the candidate of some doorplate characters extracted from the character region cannot be determined at the segmentation step, a speculation based on known knowledge about geometrical relations between each doorplate character is executed. The threshold for character extraction from candidates is adjusted when the corresponding character is rejected after classification. The data set and the images in experiments all come from practical applications. Experimental results indicate that the proposed doorplate recognition system effectively improves the recognition result.