Frequency-based object orientation and scaling determination

A major disadvantage of image retrieval systems is their lack of objects orientation and scaling matching. This paper addresses the issue of accurate, effective, computationally efficient, fast and fully-automated 2D object orientation and scaling determination. The approach relies on the objects frequency-based features. The frequency-based features used by the proposed technique, are extracted by a 2D physics-based deformable model that parameterizes the objects shape. The method was evaluated on synthetic and real images. The experimental results demonstrate the accuracy of the method, both in orientation and the scaling estimations

[1]  B. S. Manjunath,et al.  Edge flow: A framework of boundary detection and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  Nicholas Ayache,et al.  Frequency-Based Nonrigid Motion Analysis: Application to Four Dimensional Medical Images , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  K. Bathe Finite Element Procedures , 1995 .

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

[5]  Vittorio Castelli,et al.  Image Databases: Search and Retrieval of Digital Imagery , 2002 .

[6]  Ioannis Pitas,et al.  Fast free-vibration modal analysis of 2-D physics-based deformable objects , 2005, IEEE Transactions on Image Processing.

[7]  Alex Pentland,et al.  Modal Matching for Correspondence and Recognition , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Hans-Peter Kriegel,et al.  State-of-the-Art in Content-Based Image and Video Retrieval , 2001, Computational Imaging and Vision.