Color and grey level object retrieval using a 3D representation of force histogram

Abstract A new method for both grey level and color object retrieval is presented in this paper. Our feature is based on previous works on force histogram notion which is extended here to handle with photometric information. This kind of feature has low computing time and allows keeping fundamental geometric transformations as scale, translation, symmetry and rotation. More precisely objects processed by defining a tridimensional signature which takes into account their photometric variations and their shapes. Experimental results show the promising aspect of our approach.

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

[2]  William E. Higgins,et al.  Design of multiple Gabor filters for texture segmentation , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[3]  Josef Bigün,et al.  Orientation radiograms for image retrieval: an alternative to segmentation , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[4]  John P. Oakley,et al.  Storage and Retrieval for Image and Video Databases , 1993 .

[5]  Nozha Boujemaa,et al.  Retrieving Images by Content: The Surfimage System , 1998, Multimedia Information Systems.

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

[7]  W. Niblack,et al.  Image Storage and Retrieval Systems , 1992 .

[8]  Alex Pentland,et al.  Photobook: tools for content-based manipulation of image databases , 1994, Electronic Imaging.

[9]  Faouzi Ghorbel,et al.  Invariant content-based image retrieval using a complete set of Fourier-Mellin descriptors , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[10]  Marie-Christine Jaulent,et al.  A general approach to parameter evaluation in fuzzy digital pictures , 1987, Pattern Recognit. Lett..

[11]  Rajiv Mehrotra,et al.  Similar-Shape Retrieval in Shape Data Management , 1995, Computer.

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

[13]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Hiroshi Murase,et al.  Real-time 100 object recognition system , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

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

[16]  Raghaven Manmatha,et al.  Computing local and global similarity in images , 1998, Electronic Imaging.

[17]  Laurent Wendling,et al.  Fast and robust recognition of orbit and sinus drawings using histograms of forces , 2002, Pattern Recognit. Lett..

[18]  Th. Gevers,et al.  Color Image Invariant Segmentation and Retrieval , 1996 .

[19]  Tom Minka,et al.  Vision texture for annotation , 1995, Multimedia Systems.

[20]  Forouzan Golshani,et al.  ImageRoadMap: A New Content-based Image Retrieval System , 1997, DEXA.

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

[22]  Jack Bresenham,et al.  Algorithm for computer control of a digital plotter , 1965, IBM Syst. J..

[23]  Ramesh Jain,et al.  Storage and Retrieval for Image and Video Databases III , 1995 .

[24]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  James M. Keller,et al.  Quantitative analysis of properties and spatial relations of fuzzy image regions , 1993, IEEE Trans. Fuzzy Syst..

[26]  Shih-Fu Chang,et al.  Querying by color regions using VisualSEEk content-based visual query system , 1997 .

[27]  T. Lonnestad.  A new set of texture features based on the Haar transform , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[28]  R. Srihari.  Multimedia input in automated image annotation and content-based retrieval , 1995, Electronic Imaging.

[29]  Laurent Wendling,et al.  A New Way to Represent the Relative Position between Areal Objects , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Michael Stonebraker,et al.  Chabot: Retrieval from a Relational Database of Images , 1995, Computer.

[31]  S. Bhattacharjee.  A computational approach to image retrieval , 1999 .

[32]  Alex Pentland,et al.  Photobook: tools for content-based manipulation of image databases , 1994, Other Conferences.

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

[34]  Mark S. Nixon,et al.  Statistical geometrical features for texture classification , 1995, Pattern Recognit..

[35]  Shih-Fu Chang,et al.  Single color extraction and image query , 1995, Proceedings., International Conference on Image Processing.

[36]  Babu M. Mehtre,et al.  STAR-A System for Trademark Archival and Retrieval , 1995 .

[37]  Ramesh C. Jain,et al.  A survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video , 2002, Pattern Recognit..