Biometric signature verification system based on freeman chain code and k-nearest neighbor

Aini Najwa Azmi,Fakhrul Syakirin Omar,Dewi Nasien

doi:10.1007/s11042-016-3831-2

Aini Najwa Azmi, Fakhrul Syakirin Omar + Show 1 more

Open Access

https://doi.org/10.1007/s11042-016-3831-2

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Abstract

Signature is one of human biometrics that may change due to some factors, for example age, mood and environment, which means two signatures from a person cannot perfectly matching each other. A Signature Verification System (SVS) is a solution for such situation. The system can be decomposed into three stages: data acquisition and preprocessing, feature extraction and verification. This paper presents techniques for SVS that uses Freeman chain code (FCC) as data representation. Before extracting the features, the raw images will undergo preprocessing stage; binarization, noise removal, cropping and thinning. In the first part of feature extraction stage, the FCC was extracted by using boundary-based style on the largest contiguous part of the signature images. The extracted FCC was divided into four, eight or sixteen equal parts. In the second part of feature extraction, six global features were calculated against split image to test the feature efficiency. Finally, verification utilized Euclidean distance to measured and matched in k-Nearest Neighbors. MCYT bimodal database was used in every stage in the system. Based on the experimental results, the lowest error rate for FRR and FAR were 6.67 % and 12.44 % with AER 9.85 % which is better in term of performance compared to other works using that same database.

Highlights

Biometrics verification is a subject on the identification and verification of humans by their characteristics or traits
The lowest distance between feature vector of input image and stored feature vectors is computed by using Euclidean distance and its related signature class is specified
The lowest FRR, 6.67 %, is obtained from four chain code division for unsplit image, while the lowest FAR is from sixteen chain code division which is 12 %

Summary

Introduction

Biometrics verification is a subject on the identification and verification of humans by their characteristics or traits. Biometrics is widely utilized in computer science as a form of access control and identification. Similar to other human biometrics, the system compares the signature information with all the images stored in the database [2]. It can be done by comparing one-to-one process that includes data acquisition and preprocessing, feature extraction and verification. It is very important in forensic, security and resource access control such as banking, money scam, marriage approval and user access devices

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