The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
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Feature Extraction of Shape of Image Objects in Content-based Image Retrieval

내용기반으로한 이미지 검색에서 이미지 객체들의 외형특징추출

  • Cho, June-Suh (Dept. of Business Administration, Hankuk University of Foeign Studies)
  • 조준서 (한국외국어대학교 경영학과)
  • Published : 2003.12.01
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Abstract

The main objective of this paper is to provide a methodology of feature extraction using shape of image objects for content-based image retrieval. The shape of most real-life objects is irregular, and hence there is no universal approach to quantify the shape of an arbitrary object. In particular. electronic catalogs contain many image objects for their products. In this paper, we perform feature extraction based on individual objects in images rather than on the whole image itself, since our method uses a shape-based approach of objects using RLC lines within an image. Experiments show that shape parameters distinctly represented image objects and provided better classification and discrimination among image objects in an image database compared to Texture.

이 논문의 주요 목적은 내용을 기반으로 하는 이미지 검색에서 이미지 객체의 외형특징을 추출하는 방법을 제시하는 것이다. 대부분의 실질적인 객체들의 외형은 불규칙적이고, 이러한 객체를 수치화하기위한 일반적인 방법은 없다. 특히 전자 카타로그들은 상품들을 나타내는 많은 이미지를 포함하고 있다. 이 논문에서는 이미지 전체가 아닌 이미지내의 개별 객체들을 기반으로 특징을 추출하는 방법을 제시한다. 왜냐하면 제시된 방법은 한 이미지내에서 RLC lines을 사용하여 각 객체들의 외형을 기반으로하는 방법을 사용하기 때문이다. 실험결과는 일반적으로 가장 많이 사용하는 특징인 Texture와 비교를 했고 제시된 외형을 나타내는 변수들이 전자카타로그의 이미지 객체들을 뚜렷하게 나타냈고, 보다 정확하게 객체들을 분류하고 구별하였다.

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References

  1. J. R. Bach, C. Fuller, A. Gupta, A. Hampapur, B. Horowitz, R. Humphrey, R. Jain and C. Shu, The Virage image search engine : An open framework for image management, In Storage and Retrieval for Still Image and Video Databases, 1996 https://doi.org/10.1117/12.234785
  2. P. Brodatz, Textures ; a photographic album for artists and designers, Doer Publications, 1966
  3. Shi-Kuo Chang, Principles of Pictorial Information Systems Design Prentice Hall, 1989
  4. S.-K. Chang and E. Jungert, Symbolic Projection for Image Information Retrieval and Spatial Reasoning, Academic Press, 1996
  5. W. Equitz, Retrieving images from a database using texture algorithms from the QBIC system, IBM Technical Report, 1993
  6. C. Faloutsos, W. Equitz, M. Flickner, W. Niblack, D. Pekovic and R. Barber, Efficient and effective querying by image content, IBM Technical Report, 1993
  7. M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele and P. Yanker, Query by Image and Video Content : The QBIC System, IEEE Computer, 28, pp.40-56, 1995 https://doi.org/10.1109/2.410146
  8. Robert M. Haralick and Linda G. Shapiro, Computer and Robot Vision Addison Wesley, 1992
  9. M. A. Ireton and C. S. Xyedeas, Classification of Shape for Content Retrieval of Images in a Multimedia Database, In Proceedings of the Sixth International Conference on Digital Processing of Signals in Communication, 1991
  10. H. V. Jagadish, A Retrieval Technique for Similar Shapes, In ACM SIGMOD '91, 1991 https://doi.org/10.1145/115790.115821
  11. Erland Jungert, Run length code sn object-oriented sp tiald ta structure, In Proceedings of IEEE workshop on language and automation, 1986
  12. W. Li, K. S. Cadan, K. Hirata and Y. Hara, SEMCOG : An Object-based image Retrieval System and Its Visual Query Interface, In ACM SIGMOD '97, 1997 https://doi.org/10.1145/253262.253384
  13. S. Mehrotra, Y. Rui, K. Chakrabarti, M. Ortega and T. Huang, Multimedia analysis and retrieval system, In The 3rd International Workshop on Information Retrieval Systems, 1997
  14. A. Natsev, R. Rastogi and K. Shim, WALUS : A Similarity Retrieval Algorithm for Image Databases, In ACM SIGMOD International Conference on Management of Data, 1999
  15. W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glassman, D. Petkovic, P. Yanker, C. Faloutsos and G. Taubin, The QBIC Project : Querying Images by Content Using Color, Texture and Shape, In Proceedings of the SPIE Conference on Storage and Retrieval for Image and Video Databases, pp.173-187, 1993 https://doi.org/10.1117/12.143648
  16. V. E. Ogle and M. Stonebraker, Chabot : Retrieval from a Relational Database of Images, IEEE Computer, 28(9), pp. 40-56, 1995 https://doi.org/10.1109/2.410150
  17. A. Pentland R. W. Picard and S. Sclaro, Photobook : Tools for Content-Based Manipulation of Image Databases. In Proceedings of the SPIE Storage and Retrieval Image and Video Databases II, 1994 https://doi.org/10.1117/12.171786
  18. John C. Russ, The Image Processing Handbook, CRC Press, 3rd edition, 1998
  19. John R. Smith and Shi-Fu Chang, Automated Image Retrieval Using Color and Texture, Columbia Technical Report, 1995
  20. John R. Smith and Shi-Fu Chang, VisualSEEK : A Fully Automated Content-Based Image Query System, In ACM Multimedia 96, 1996
  21. D. Unwin. Introductory Spatial Analysis, Methuen, London, 1981