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

Authors:
Kwang-Baek Kim;Sungshin Kim
Affiliations:
Department of Computer Engineering, Silla University, Busan 617-736, Republic of Korea;School of Electrical Engineering, Pusan National University, Busan 609-735, Republic of Korea
Venue:
Neurocomputing
Year:
2008

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Abstract

In this paper, passport recognition and face verification methods which can automatically recognize passport codes and discriminate forgery passports to improve efficiency and systematic control of immigration management are proposed. Adjusting the slant is very important for recognition of characters and face verification since slanted passport images can bring various unwanted effects to the recognition of individual codes and faces. Therefore, after smearing the passport image, the longest extracted string of characters is selected. The angle adjustment can be conducted by using the slant of the straight and horizontal line that connects the center of thickness between left and right parts of the string. Extracting passport codes is done by Sobel operator, horizontal smearing, and 8-neighborhood contour tracking algorithm. The string of codes can be transformed into binary format by applying repeating binary method to the area of the extracted passport code strings. The proposed radial basis function (RBF) network is applied to the middle layer of RBF network by using the fuzzy logic connection operator and proposing the enhanced fuzzy adaptive resonance theory (ART) algorithm that dynamically controls the vigilance parameter. After several tests using a forged passport and the passport with slanted images, the proposed method was proven to be effective in recognizing passport codes and verifying facial images.