An Abstract Image Representation Based on Edge Pixel Neighborhood Information (EPNI)

In this paper we introduce a new abstract image representation based on Edge Pixel Neighborhood Information (EPNI). It is applied in image retrieval problem when user query is a fast drawn, rough example. The representation consists of two main elements. Aneigh borhood vector f and a vicinity table v. The former contains the frequencies of edge pixels with similar directions and the latter holds information about neighboring edge directions. An image similarity measure based on EPNI components is also designed and compared with some other measures known from the literature. Experimental results show a good recognition accuracy in a data set containing a wide range of color images.

[1]  Daniel P. Huttenlocher,et al.  Comparing images using the Hausdorff distance under translation , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  Shih-Fu Chang,et al.  VisualSEEk: a fully automated content-based image query system , 1997, MULTIMEDIA '96.

[3]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Alberto Del Bimbo,et al.  Visual information retrieval , 1999 .

[5]  Erkki Oja,et al.  Statistical Shape Features for Content-Based Image Retrieval , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[6]  Mohamed Abdel-Mottaleb.  Image retrieval based on edge representation , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[7]  Miroslaw Bober,et al.  MPEG-7 visual shape descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[8]  Christos Faloutsos,et al.  QBIC project: querying images by content, using color, texture, and shape , 1993, Electronic Imaging.

[9]  Toshikazu Kato,et al.  Query by Visual Example - Content based Image Retrieval , 1992, EDBT.

[10]  Anil K. Jain,et al.  Image retrieval using color and shape , 1996, Pattern Recognit..

[11]  B. S. Manjunath,et al.  Color and texture descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[12]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  C. Won,et al.  Efficient Use of MPEG‐7 Edge Histogram Descriptor , 2002 .

[14]  Alex Pentland,et al.  Photobook: Content-based manipulation of image databases , 1996, International Journal of Computer Vision.

[15]  Shih-Fu Chang,et al.  MetaSEEk: a content-based metasearch engine for images , 1997, Electronic Imaging.

[16]  Tom Minka,et al.  Interactive learning with a "Society of Models" , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.