매개변수적 서명 검증에서 개인화된 특징 집합의 가중치 유클라드 거리 산출 기법

• 영문명: A Technique of Calculating a Weighted Euclidean Distance with a Personalized Feature Set in Parametric Signature Verification
• 발행기관: 한국시뮬레이션학회
• 저자명: 김성훈(Seong Hoon Kim)
• 간행물 정보: 『한국시뮬레이션학회 논문지』제14권 제3호, 137~146쪽, 전체 10쪽
• 주제분류: 공학 > 기타공학
• 파일형태: PDF
• 발행일자: 2005.09.30

영문 초록

In parametric approach to a signature verification, it generally uses so many redundant features unsuitable for each individual signature that it causes harm, instead. This paper proposes a method of determining personalized weights of a feature set in signature verification with parametric approach by identifying the characteristics of each feature. For an individual signature, we define a degree of how difficult it is for any other person to forge the one s (called DFD as the Degree of Forgery Difficulty). According to the statistical characteristics and the intuitional characteristics of each feature, the standard features are classified into four types. Four types of DFD functions are defined and applied into the distance calculation as a personalized weight factor. Using this method, the error rate of signature verification is reduced and the variation of the performance is less sensitive to the changes of decision threshold.

목차

1. 서론

2. 특징 선택(Feature Selection)

3. 개인별 가중치 설정 방법

4. 실험 및 비교

5. 결론

참고문헌

키워드

weighted euclidean distance parametric signature verification personalized feature set forgery difficulty degree