Methods and devices for indexing and searching for digital...

Details Methods and devices for indexing and searching for digital... Methods and devices for indexing and searching for digital...

2006-09-05

2006-09-05

Bali, Vikkram (Department: 2624)

Image analysis

Image transformation or preprocessing

Image storage or retrieval

C382S190000

Reexamination Certificate

active

07103237

ABSTRACT:
According to the invention, a method of indexing a digital image comprises the following steps: generating a first information item (H(Im)) characteristic of the visual content of the image (Im) to be indexed; generating a second information item (W(Im)) characteristic of the spatial distribution of the visual content of the image (Im) in its image plane; and associating, with the image (Im), an index (IDX(Im)) composed of the first information item (H(Im)) and the second information item (W(Im)).More particularly, the step of generating the first information item (H(Im)) has the following substeps: dividing the image plane of the image (Im) according to a partitioning comprising a predefined number N of blocks (Bi); extracting, from each of the blocks (Bi), a data item of a first type (hiIm) representing at least one characteristic of the visual content of the block under consideration; and generating the first information item (H(Im)) as being a vector having N components, each of which is one of the data items of the first type (hiIm).

REFERENCES:
Shih Fu Chang and John R. Smith. “Extracting Multi-Dimensional Signal Features for Content-Based Visual Query”. May 1995 SPIE Symposium on Visual Communications adn Signal Processing. pp. 1-12.
Kai-Chieh Liang and Jay Kuo. “WaveGuide: A Joint Wavelet-Based Image Representation and Description System”. Nov. 1999. IEEE Transactions on Image Processing vol. 8, No. 11. pp. 1619-1629.
Andre Folkers. Ph D. Thesis “Pictorial Query Specification and Processing ”. Jan. 2000. pp. 1-178.
John. R. Smith. Ph D. Thesis “Integrated Spatial and Feature Image Systems: Retieval, Analysis and Compression”. 1997. pp. 1-75.
J.R. Smith and S. Chang, “Transform Features for Texture Classification and Discrimination in Large Image Databases”. IEEE ICIP-94, 1994.
G. Van de Wouwer,“Color Texture Classification by Wavelet Energy Correlation Signatures”. ICIAP (1): 327-334, 1997.
T. Chang and J. Kuo,“Texture Analysis and Classification with Tree-Structured Wavelet Transfom”. IEEE Transactions on Image Processing, vol. 2, No. 4, Oct. 1993.
B. Moghaddam et al., “Defining Image Content with Multiple Regions-of-Interest”, IEEE Workshop on Content-Based Access o Image and Video Libraries, Jun. 1999.
D. Dupplaw et al., “Spatial Colour Matching for Content Based Image Retrieval and Navigation”, Challenge of Image Retrieval, 1999.
J. Malki et al., “Region Queries without Segmentation for Image Retrieval by Content”, International Conference on Visual Information Systems (VISUAL'99), Lecture Notes in Computer Science vol. 1614, pp. 115-122., Jun. 1999.
A. Folkers et al., “Processing Pictorial Queries with Multiple Instances using Isomorphic Subgraphs”, Proceedings of the 15th International Conference on Pattern Recognition, vol. 4, No. 3-7, Sep. 2000.
J.R. Ullmann, “An Algorithm for Subgraph Isomorphism”, JACM vol. 23, Issue 1, Jan. 1976.
J. Lee and B. Dickinson,“Multiresolution Video Indexing For Subband Coded Video Databases”, Proceedings of IS&T/SPIE, Conference on Storage and Retrieval for Image and Video Databases, 1994.
J. Huang et al., “Image Indexing Using Color Correlograms”, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997.
J.R. Smith and S. Chang,“Tools and Techniques for Color Image Retrieva”I, IS&T/SPIE Proceedings vol. 2670, Storage & Retrieval for Image and Video Databases IV, 1996.
J.R. Smith and S. Chang,“ Local Color and Texture Extraction and Spatial Query”, Proceedings of the International Conferenc on Image Processing, 1996.
J.R. Smith and S. Chang, “VisualSEEk: A Fully Auotmated Content-Based Image Query System”, ACM Multimedia '96, 1996.
J.R. Bach et al., “The Virage Image Search Engine: An Open Framework for Image Management”, SPIE vol. 2670, Mar. 1996.
Flickner et al., “Query by Image and Video Content: The QBIC System”, IEEE Computer Magazine, Sep. 1995.
C. Nastar et al., “SurfImage: A Flexible Content-Based Image Retrieval System”. ACM Multimedia '98, 1998.
S. Sclaroff et al., “ImageRover: A Content-Based Image Browser for the World-Wide Web”, Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries, Jun. 1997.
R. Milanese et al., “Correspondence Analysis and Hierarchical Indexing for Content-Based Image Retrieval”, Proceedings of th Information Conference on Image Processing, 1996.
R. Manmatha et al., “On Computing Local and Global Similarity in Images”, Technical Report MM-25, Center for Intelligent Information Retrieval, Computer Science Dept., University of Massachusetts, Amherst, Massachusetts, 1998.
A. Jain et al., “Image Retrieval Using Color and Shape”, Pattern Recognition 29 (8), pp. 1233-1244, 1996.
A, Del Bimbo et al., “Using Weighted Spatial Relationships in Retrieval by Visual Contents”, Proceedings of the IEEE Worksho on Content—Based Access of Image and Video Libraries, 1998.
R. Veltkamp et al., “Content-Based Image Retrieval Systems: A Survey”, Oct. 2002.
Ko et al. “Image retrieval using flexible image subblocks”. Proceedings of the 2000 ACM symposium on Applied computing—vol. 2, Mar. 2000, pp. 574-578.
Stricker et al. “Similarity of Color Images”, SPIE: Storage Retrieval and Video Database III, vol. 2420, Feb. 1995, pp. 381-392.
Celentano, A., et al., “Feature Integration and Relevance Feedback Analysis in Image Similarity Evaluation,” Journal of Electronic Imaging, U.S. SPIE + IS&T, vol. 7, No. 12 (Apr. 1, 1998), pp. 308-317, XP000750386 ISSN: 1017-9909.
Yamomoto, H., et al., “Content-Based Similarity Retrieval of Images Based on Spatial Color Distributions”Proceedings of the International Conference on Imag Analysis and Proceedings, (Jul. 27, 1999), pp. 951-956, XP002137676.
Institute of Electrical and Electronics Engineers: “An Image Database System With fast Image Indexing Capability Based on Color Histograms”, Proceedings of the Region 10 Annual International Conference (TENCON), New York, U.S., IEEE, vol. Conf. 9 (Jul. 27, 1999), pp. 407-411, XP000529510, ISBN: 0-7803-1863-3.
Williams, R., “The Goblin Quadtree”, Computer Journal, GB, Oxford University Press, Surrey, vol. 31, No. 4 (Aug. 1, 1988), pp. 358-363, XP000743648, ISSN: 0010-4620.
Lee, J., et al., “Multiresolution Video Indexing For Subband Video Databases,” Dept. of Electrical Engineering, Princeton University, Princeton, N.J. 08544, Proc. of SPIE, vol. 2185 (Feb. 1994), pp. 162-170.
Swain, M. J., et al., “Color Indexing,” International Journal of Computer Vision, 7:1 (1991), pp. 11-32.
Sm ith, J. R., et al., “Quad-Tree Segmentation for Texture-Based Query,” Center for Telecommunications Research and Electrical Engineering Department, Columbia University, New York, N.Y. 10027, Proc. ACM 2ndMultimedia Conference, San Fran., CA (Oct. 1994), pp. 279-285.
Messmer, B. T., et al., “Subgraph Isomorphism in Polynomial Time,” Thesis, University of Bern, Bern, Switzerland (Nov. 1995), pp. 1-33.

Affiliated with

Also associated with

Rating

Methods and devices for indexing and searching for digital... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Methods and devices for indexing and searching for digital..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Methods and devices for indexing and searching for digital... will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3615727