Earticle

현재 위치 Home

An Efficient Algorithm for Facial Image Classification

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSIP) 바로가기
  • 간행물
    International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
  • 통권
    Vol.8 No.12 (2015.12)바로가기
  • 페이지
    pp.121-134
  • 저자
    Dr.S.Vijayarani, M.Vinupriya
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A270044

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

원문정보

초록

영어
Image mining is one of the data mining research areas and it can be defined as getting hidden information from the image databases. It is used to identify unknown patterns, inherent and valuable information from images. Image mining helps to make relationships between various categories of images which are found in large image databases. These images can reveal useful information to the users. Image mining is distinct from low-level computer vision and image processing techniques. It uses methods from computer vision, image retrieval, image processing, data mining, database, machine learning, and artificial intelligence. Although all these subjects study the same object image, the vital difference between image data mining and the other subjects is, image data mining focuses on large scale set of images while image processing and pattern recognition analysis are based on only single image. Face detection is the problem of determining whether a sub-window of an image contains a face. It has received much attention and has been an extensive research topic in recent years. In this research work, facial images are classified based on its shape feature using optimization algorithms. A new algorithm, i.e. classification based similarity finding is proposed for classifying the facial images as round or oval shape. The performance of the proposed classification based similarity algorithm is compared with the particle swam optimization and genetic algorithms. The results of the existing and proposed algorithms are analyzed based on accuracy and execution time factors. From this we observed that the proposed classification based similarity finding algorithm has produced good results.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Proposed Work
  3.1. Preprocessing
  3.2. Segmentation
  3.3. Edge Detection
  3.4. Classification
  3.5. Particle Swarm Optimization
  3.6. Genetic Algorithm
  3.7. Selection Operator
  3.8. Crossover
  3.9. Mutation
  3.10. Classification by Similarity Finding
 4. Experimental Results
 5. Conclusion
 References

키워드

Image mining Edge detection PSO GA Classification based Similarity Finding

저자

  • Dr.S.Vijayarani [ Assistant Professor, Bharathiar University, Coimbatore ] Corresponding Author
  • M.Vinupriya [ M. Phil Research Scholar, Bharathiar University, Coimbatore ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    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 505 DDC 605

이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8 No.12

    피인용수 : 0(자료제공 : 네이버학술정보)

    함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.

      페이지 저장