Selecting appropriate feature extraction method is absolutely one of the most important factors to archive high classification performance in pattern recognition systems. Among different feature extraction methods proposed for pattern recognition, statistical moments seem to be so promising. Whereas theoretical comparison of the moments is too complicated, in this paper, an experimental evaluation on four well known statistical moments namely Hu invariant moments, Affine invariant moments, Zernike moments, and Pseudo-Zernike moments is presented. Set of different experiments on a binary images dataset consisting of regular, translated, rotated, and scaled Persian printed numerical characters using a nearest neighbor rule classifier has been done and variety of interesting results have been presented. Finally, the results show that Pseudo-Zernike moments outperform the other introduced moments.
목차
Abstract 1. Introduction 2. Theory of Moments 2.1. Hu Invariant Moments 2.2. Affine Moment Invariants 2.3. Zernike Moments 2.4. Pseudo-Zernike Moments 3. Implementation Details 3.1. The Utilized Dataset 3.2. Nearest Neighbor Rule Classifier 4. Experimental Results 5. Conclusion References
키워드
Feature extractionoptical character recognitionpattern recognitionstatistical moments.
저자
Hamid Reza Boveiri [ Faculty Member, Sama College, Islamic Azad University, Shushtar Branch Member, Young Researchers Club, Islamic Azad University, Shushtar Branch ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition vol.3 no.4