The work is dedicated to development of algorithms to increase the efficiency of character recognition on a complex background with noise, affine and projective distortions. The paper proposes an approach to solving the problem of character recognition, which includes three main stages: detection of region character locations in the image; image normalization and selection of individual characters; character recognition. The ViolaJones algorithm realization is proposed for detecting of the characters' region in images with complex background. Image normalization includes the following operations: selection borders, Hough transform, closed contours search, image alignment. The search of characters string horizontal edges in the image is performed by using the Hough transform. The detection of individual characters' regions is performed by using the closed contours search. The configuration of convolution neural network is proposed for character recognition. The testing results of the developed algorithms efficiency and their comparison with existing analogues are presented. On the basis of the approach, the software system which shows the high efficiency of character recognition on a complex background intended to recognize the car number plates in the images was developed.
|Состояние||Опубликовано - 2016|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition