Normalised Euclidean Distance Based Image Retrieval Using Coefficient Analysis

  • Nilofar Khan
  • Wasim Khan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 177)


The article presented a novel method based on normalized Euclidean distance using application of discrete wavelet transform and bins intensity measurement, which is then coupled to a parameterized framework for content-based image retrieval. The discrete wavelet transform captures both frequency and location information and make image retrieval efficient. It further facilitates to incorporate recent research work on feature based coefficient distributions. We demonstrate the applicability of the proposed method in the context of color texture retrieval on different image databases and compare retrieval performance to a collection of state-of-the-art approaches in the area. Our experiment results on a large database further include a thorough analysis of computations of the main building blocks and runtime measurements of images.


Content based image retrieval discrete wavelet transform Euclidean distance Bins intensity measurement Texture feature Color feature 


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  1. 1.
    Chang, N.-S., Fu, K.-S.: Query by pictorial example. IEEE Transactions on Software Engineering 6(6), 519–524 (1980)CrossRefGoogle Scholar
  2. 2.
    Smeulders, A.W.M., Woming, S., Santini, S., Gupta, A., Jain, R.: Content-Based Image Retrieval at the End of the Early Years. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(12), 1349–1380 (2000)CrossRefGoogle Scholar
  3. 3.
    Khan, W., Gupta, S.K.N., Khan, N.: A Proposed Method for Image Retrieval using Histogram values and Texture Descriptor Analysis. International Journal of Soft Computing and Engineering (IJSCE) I(II) (May 2011) ISSN: 2231-2307Google Scholar
  4. 4.
    Singhai, N., Shandilya, S.K.: A Survey On: Content Based Image Retrieval Systems. International Journal of Computer Applications (0975 – 8887) 4(2) (July 2010)Google Scholar
  5. 5.
    Zhang, J., Hsu, W., Li Lee, M.: An Information-Driven Framework for Image Mining. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 232–242. Springer, Heidelberg (2001), doi:10.1007/3-540-44759-8_24CrossRefGoogle Scholar
  6. 6.
    Sheila Angeli Marcos, M., Soriano, M., Saloma, C.: Low-Level Color and Texture Feature Extraction of Coral Reef Components (2007)Google Scholar
  7. 7.
    Srinivasa Rao, C., Srinivas Kumar, S., Chatterji, B.N.: Content Based Image Retrieval using Contour let TransformGoogle Scholar
  8. 8.
    Das, A.: Entropy-Based Indexing On Color And Textur. In: Image RetrievalGoogle Scholar
  9. 9.
    Yu, H., Li, M., Zhang, H.-J., Feng, J.: Color Texture Moments For Content Based Image RetrievalGoogle Scholar
  10. 10.
    Bdesselam, A., Wang, H.H., Arayanan, K.: Spiral Bit-string Representation of Color for Image RetrievalGoogle Scholar
  11. 11.
    Histogram Re nement for Content-Based Image Retrieval, Greg Pass Ramin Zabih Google Scholar
  12. 12.
    Tamura’s Texture FeaturesGoogle Scholar
  13. 13.
    Nirmal, S.: Proceedings of the 3rd National Conference; INDIA Com-2009 Computing For Nation Development, February 26-27, Bharti Vidhyapeet ’s Institute of Computer Applications and management, New Delhi. Content Based Image Retrieval Techniques (2009)Google Scholar
  14. 14.
    Ganeshwara Rao, N., Vijaya Kumar, V., Venkata Krishna, V.: Texture Based Image Indexing and Retrieval. IJCSNS International Journal of Computer Science and Network Security 9(5) (May 2009)Google Scholar
  15. 15.
    Kavitha, C., Prabhakara Rao, B., Govardhan, A.: An Efficient Content Based Image Retrieval Using Color And Texture of Image Subblocks. International Journal of Engineering Science and Technology (IJEST) 3(2) (February 2011)Google Scholar
  16. 16.
    Sharma, N., Rawat, P., Singh, J.: Efficient CBIR Using Color Histogram Processing. Signal & Image Processing: An International Journal (SIPIJ) 2(1) (March 2011)Google Scholar
  17. 17.
    Reddy, P.V.N., Sataya Prasad, K.: Content Based Image Retrieval Using Local Derivative Patterns. 28(2) (June 30, 2011)Google Scholar
  18. 18.
    Reddy, P.V.N., Satya Prasad, K.: Multiwavelet Based Texture Features for Content Based Image Retrieval. IJCST 2(1) (March 2011) ISSN : 2229 - 4333 ( Print ) | ISSN : 0976-8491(Online)Google Scholar
  19. 19.
    Jeong, S.: Histogram-Based Color Image Retrieval. Psych221/EE362 Project Report (March 15, 2001)Google Scholar
  20. 20.
    Long, F., Zhang, H., Feng, D.D.: Fundamentals Of content-Based image RetrievalGoogle Scholar
  21. 21.
    Naresh Babu, K., Pothalaiah, S., Ashok Babu, K.: Image Retieval Color, Shape And Texture Features Using Content Based. International Journal of Engineering Science and Technology 2(9), 4278–4287 (2010)Google Scholar
  22. 22.
    Rao, B., Prabhakara Rao, B., Govardhan, A.: Content Based Image Retrieval using Dominant Colorand Texture features. (IJCSIS) International Journal of Computer Science and Information Security 9(2) (February 2011)Google Scholar
  23. 23.
    Kharate, G.K., Patil, V.H., Bhale, N.L.: Selection of Mother Wavelet For Image Compression on Basis of Nature of Image. Journal of Multimedia 2(6) (November 2007)Google Scholar
  24. 24.
    Khokher, A., Talwar, R.: Image Retrieval: A State Of The Art Approach For Cbir. International Journal Of Engineering Science And Technology (IJEST)Google Scholar
  25. 25.
    Karthikeyani, V., Duraiswamy, K., Kamalakkannan, P.: Conversion of Gray-scale image to Color Image with and without Texture Synthesis. IJCSNS International Journal of Computer Science and Network Security 7(4) (April 2007)Google Scholar
  26. 26.
    Suhasini, P.S., Sri Rama Krishna, K., Murali Krishna, I.V.: CBIR Using Color Histogram Processing. Journal of Theoretical and Applied Information TechnologyGoogle Scholar
  27. 27.
    Lakshmi Devasena, C., Sumathi, T., Hemalatha, M.: An Experiential Survey on Image Mining Tools,Techniques and Applications. International Journal on Computer Science and Engineering (IJCSE)Google Scholar
  28. 28.
    Lawrence Zitnick, C., Kanade, T.: Content-Free Image Retrieval (May 2003)Google Scholar
  29. 29.
    Grosky, W.I.: Image Retrieval - Existing Techniques, Content-Based (Cbir) Systems,
  30. 30.
    Zhao, R., Grosky, W.I.: PART II:Content-Based Retrieval And Image Database techniques,

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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Information TechnologyUniversity of RGPV Bhopal Chameli Devi School of EngineeringIndoreIndia
  2. 2.Department of Computer ScienceUniversity of RGPV Bhopal Govt. Women’s Polytechnic CollegeIndoreIndia

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