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Image Retrieval Process Based on Relevance Feedback and Ontology Using Decision Tree

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJMUE) 바로가기
  • 간행물
    International Journal of Multimedia and Ubiquitous Engineering SCOPUS 바로가기
  • 통권
    Vol.10 No.10 (2015.10)바로가기
  • 페이지
    pp.83-90
  • 저자
    Debnath Bhattacharyya, Dipankar Hazra, Tai-hoon Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A257260

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원문정보

초록

영어
In this paper, another strategy for immediate features based image recovery is proposed. Image database is developed with low level texture features got from Gray Level Co- Occurrence Matrix (GLCM) and measurable techniques for Tamura. Semantic level inquiries from the user mapped to the low level peculiarities at recovery time to recover the required images. Images with more than one moderate features can be recovered by utilizing intersection of images recovered by each of the queried feature. Artificial Neural Network (ANN) is utilized as a part of the following steps in the wake of accepting user inputs. In spite of the fact that semantics are utilized as search key as a part of the beginning steps, low level features are utilized as a part of the ANN based searching in later steps. Back propagation Algorithm is utilized as a part of learning step. This ANN based relevance feedback technique enhances accuracy of immediate feature based image retrieval method. Decision tree (DT) can likewise be connected in relevance feedback stage. Decision tree is framed in training stage and images will be tested by of the decision tree. Relation storing ontology related information is utilized as a part of every phase of retrieval procedure to evacuate ambiguities identified with synonyms and hypernym-homonym sets.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed System
  3.1. Low Level Texture Features’ Extraction and Storage
  3.2. Image Retrieval by SQL
  3.3. Relevance Feedback for Image Retrieval
  3.4. Image Retrieval using Ontology Mapping
 4. Results
 5. Conclusion
 References

키워드

Semantic Based Image Retrieval intermediate feature Neural network based image retrieval Decision Tree based image retrieval SQL based image retrieval relevance feedback based image retrieval Ontology in image retrieval

저자

  • Debnath Bhattacharyya [ Department of Information Technology, Bharati Vidyapeeth University College of Engineering, Pune-411043, India ]
  • Dipankar Hazra [ Computer Science and Engineering Department, Om Dayal Group of Institutions, Howrah-711316, WB, India ]
  • Tai-hoon Kim [ Department of Convergence Security, Sungshin Women's University, 249-1, Dongseon-dong 3-ga, Seoul, 136-742, Korea ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
  • 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 Multimedia and Ubiquitous Engineering
  • 간기
    월간
  • pISSN
    1975-0080
  • 수록기간
    2008~2016
  • 등재여부
    SCOPUS
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.10 No.10

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