Recognition of passports using a hybrid intelligent system

Authors:
Kwang-Baek Kim;Sungshin Kim;Sang-An Ha
Affiliations:
Dept. of Computer Engineering, Silla University, Busan, Korea;Division of Electrical Engineering, Pusan National University, Busan, Korea;Dept. of Environmental Engineering, Silla University, Busan, Korea
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

Citing 3
Cited 2

Fundamentals of digital image processing

Fundamentals of digital image processing
Neural networks for vision and image processing

Neural networks for vision and image processing
Document analysis system

IBM Journal of Research and Development

A passport recognition and face verification using enhanced fuzzy ART based RBF network and PCA algorithm

Neurocomputing
A passport recognition and face verification using enhanced fuzzy neural network and PCA algorithm

ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.