Object-Based Image Retrieval Using Active Nets

In this work, extraction of relevant objects from images and their matching for retrieval is proposed. Objects are represented by using a two dimensional deformable structure referred to as active net, capable to adapt to relevant image regions according to chromatic and edge information. In particular, this representation allows a joint description of color, shape and structural information of extracted objects. A similarity measure between active nets is also defined and validated in a set of retrieval experiments on the ETH-80 objects database

[1]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  J. Besag On the Statistical Analysis of Dirty Pictures , 1986 .

[3]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[4]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[5]  Azriel Rosenfeld,et al.  Maximum-likelihood edge detection in digital signals , 1992, CVGIP Image Underst..

[6]  Michael A. Arbib,et al.  Color Image Segmentation using Competitive Learning , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[8]  Amarnath Gupta,et al.  Visual information retrieval , 1997, CACM.

[9]  Arie E. Kaufman,et al.  Three-dimensional active net for volume extraction , 1998, Electronic Imaging.

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

[11]  Arnold W. M. Smeulders,et al.  Color-based object recognition , 1997, Pattern Recognit..

[12]  Shih-Fu Chang,et al.  Image Retrieval: Current Techniques, Promising Directions, and Open Issues , 1999, J. Vis. Commun. Image Represent..

[13]  Konstantinos N. Plataniotis,et al.  A Novel Vector-Based Approach to Color Image Retrieval Using a Vector Angular-Based Distance Measure , 1999, Comput. Vis. Image Underst..

[14]  Stefan Fischer,et al.  Face authentication with Gabor information on deformable graphs , 1999, IEEE Trans. Image Process..

[15]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Manuel G. Penedo,et al.  Automatic 3D shape reconstruction of bones using active nets based segmentation , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[17]  Arnold W. M. Smeulders,et al.  PicToSeek: combining color and shape invariant features for image retrieval , 2000, IEEE Trans. Image Process..

[18]  James Ze Wang,et al.  SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Alberto Del Bimbo,et al.  Efficient Matching and Indexing of Graph Models in Content-Based Retrieval , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Graham D. Finlayson,et al.  Color by Correlation: A Simple, Unifying Framework for Color Constancy , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Jitendra Malik,et al.  Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Bernt Schiele,et al.  Analyzing appearance and contour based methods for object categorization , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[23]  Shree K. Nayar,et al.  Reflectance based object recognition , 1996, International Journal of Computer Vision.

[24]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[25]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[26]  Gunther Heidemann,et al.  Combining spatial and colour information for content based image retrieval , 2004, Comput. Vis. Image Underst..

[27]  Bernt Schiele,et al.  Recognition without Correspondence using Multidimensional Receptive Field Histograms , 2004, International Journal of Computer Vision.

[28]  Arnold W. M. Smeulders,et al.  The Amsterdam Library of Object Images , 2004, International Journal of Computer Vision.

[29]  Hiroshi Murase,et al.  Visual learning and recognition of 3-d objects from appearance , 2005, International Journal of Computer Vision.

[30]  Ying Liu,et al.  A survey of content-based image retrieval with high-level semantics , 2007, Pattern Recognit..