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Differentiation of Signature Traits vis-à-vis Mobile- and Table- Based Digitizers
Stephen J. Elliott 한국전자통신연구원 2004 ETRI Journal Vol.26 No.6
As the use of signatures for identification purposes is pervasive in society and has a long history in business, dynamic signature verification (DSV) could be an answer to authenticating a document signed electronically and establishing the identity of that document in a dispute. DSV has the advantage in that traits of the signature can be collected on a digitizer. The research question of this paper is to understand how the individual variables vary across devices. In applied applications, this is important because if the signature variables change across the digitizers this will impact performance and the ability to use those variable. Understanding which traits are consistent across devices will aid dynamic signature algorithm designers to create more robust algorithms.
Matching Performance-Based Comparative Study of Fingerprint Sample Quality Measures
김장룡(Changlong Jin),김학일(Hakil Kim),Stephen Elliott 한국정보보호학회 2009 정보보호학회논문지 Vol.19 No.3
지문샘플의 품질은 지문인식 시스템에서 매칭 성능에 영향을 주는 중요한 요소이다. 지문인식 시스템에서 낮은 품질의 지문영상을 제거하면 인식 에러율이 현저하게 줄어드는 것을 알 수 있다. 본 논문에서는 minutiae 기반의 지문인식 알고리즘을 이용하여 단일 샘플 품질 측정방법에 대한 유효성을 평가하였다. 우선, minutiae 기반의 지문인식 알고리즘의 매칭성능에 영향을 주는 여러 가지 요소에 대하여 검증하고, 다음, 현재 흔히 사용하는 측정방법에 대해 연구하고, 그 중 효과적인 품질측정방법들을 선택하여 NIST, QualityCheck와 Verifinger 5.0을 이용하여 비교분석 하였다. FVC 데이터베이스로 실험한 결과 단일 측정방법도 매칭성능을 효과적으로 향상함을 알 수 있었다. Fingerprint sample quality is one of major factors influencing the matching performance of fingerprint recognition systems. The error rates of fingerprint recognition systems can be decreased significantly by removing poor quality fingerprints. The purpose of this paper is to assess the effectiveness of individual sample quality measures on the performance of minutiae-based fingerprint recognition algorithms. Initially, the authors examined the various factors that influenced the matching performance of the minutiae-based fingerprint recognition algorithms. Then, the existing measures for fingerprint sample quality were studied and the more effective quality measures were selected and compared with two image quality software packages, (NFIQ from NIST, and QualityCheck from Aware Inc.) in terms of matching performance of a commercial fingerprint matcher (Verifinger 5.0 from Neurotechnologija). The experimental results over various Fingerprint Verification Competition (FVC) datasets show that even a single sample quality measure can enhance the matching performance effectively.