Improving the recognition by integrating the combination of descriptors

A new method for combining shape descriptors based on a behavior study from a learning set is proposed in this paper. Each descriptor is applied on several clusters of objects or symbols. For each cluster and for any descriptor a pertinent map is directly carried out from the learning database. Then existing conflicts are assessed and integrated in such a map. At last, we show that the use of combination of descriptors enables to improve the recognition using real data.

[1]  King-Sun Fu,et al.  Shape Discrimination Using Fourier Descriptors , 1977, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Carlo Tomasi,et al.  Perceptual metrics for image database navigation , 1999 .

[3]  Majid Ahmadi,et al.  Pattern recognition with moment invariants: A comparative study and new results , 1991, Pattern Recognit..

[4]  Laurent Wendling,et al.  Binary Shape Normalization Using the Radon Transform , 2003, DGCI.

[5]  Guojun Lu,et al.  Generic Fourier descriptor for shape-based image retrieval , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[6]  JEFFREY WOOD,et al.  Invariant pattern recognition: A review , 1996, Pattern Recognit..

[7]  Arnold W. M. Smeulders,et al.  Content-based image retrieval by viewpoint-invariant color indexing , 1999, Image Vis. Comput..

[8]  Sven Loncaric,et al.  A survey of shape analysis techniques , 1998, Pattern Recognit..

[9]  Benjamin B. Kimia,et al.  Symmetry-Based Indexing of Image Databases , 1998, J. Vis. Commun. Image Represent..

[10]  Rui J. P. de Figueiredo,et al.  A general moment-invariants/attributed-graph method for three-dimensional object recognition from a single image , 1986, IEEE J. Robotics Autom..

[11]  Mario Vento,et al.  Symbol recognition in documents: a collection of techniques? , 2000, International Journal on Document Analysis and Recognition.

[12]  Faouzi Ghorbel,et al.  A complete invariant description for gray-level images by the harmonic analysis approach , 1994, Pattern Recognit. Lett..

[13]  M. Teague.  Image analysis via the general theory of moments , 1980 .

[14]  Faouzi Ghorbel,et al.  Robust and Efficient Fourier-Mellin Transform Approximations for Gray-Level Image Reconstruction and Complete Invariant Description , 2001, Comput. Vis. Image Underst..

[15]  Thomas S. Huang,et al.  A Modified Fourier Descriptor for Shape Matching in MARS , 1998, Image Databases and Multi-Media Search.

[16]  Guojun Lu,et al.  Review of shape representation and description techniques , 2004, Pattern Recognit..

[17]  Sunil Arya,et al.  An optimal algorithm for approximate nearest neighbor searching fixed dimensions , 1998, JACM.

[18]  Thomas Bernier,et al.  A new method for representing and matching shapes of natural objects , 2003, Pattern Recognit..

[19]  Matti Pietikäinen,et al.  An Experimental Comparison of Autoregressive and Fourier-Based Descriptors in 2D Shape Classification , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[21]  Ashraf A. Kassim,et al.  A comparative study of efficient generalised Hough transform techniques , 1999, Image Vis. Comput..

[22]  Alireza Khotanzad,et al.  Classification of invariant image representations using a neural network , 1990, IEEE Trans. Acoust. Speech Signal Process..

[23]  Alireza Khotanzad,et al.  Invariant Image Recognition by Zernike Moments , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Joachim M. Buhmann,et al.  Empirical Evaluation of Dissimilarity Measures for Color and Texture , 2001, Comput. Vis. Image Underst..

[26]  Faouzi Ghorbel,et al.  Robust and efficient Fourier-Mellin transform approximations for invariant grey-level image description and reconstruction , 2001 .