Contour finding in segmentation of video sequences

Image analysis – Image segmentation

Reexamination Certificate

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C382S180000, C375S240010, C345S619000

Reexamination Certificate

active

08077969

ABSTRACT:
A method of image processing includes: receiving at least one video frame of a video sequence, the at least one video frame including at least one foreground subject and a background; and processing the at least one video frame so as to separate the at least one foreground subject from the background. The processing includes: generating a pixel mask containing information indicating, for each pixel of the at least one video frame, whether the pixel belongs to the foreground subject or to the background, and determining contours of the at least one foreground subject on the pixel mask. The determining of the contours includes for each pixel in the at least one video frame; based on the information included in the pixel mask, determining whether at least one pixel border belongs to a contour of the at least one foreground subject, the at least one pixel border separating the pixel from a respective at least one adjacent pixel.

REFERENCES:
patent: 5214718 (1993-05-01), Khosla
patent: 5832115 (1998-11-01), Rosenberg
patent: 5915044 (1999-06-01), Gardos et al.
patent: 6625310 (2003-09-01), Lipton et al.
patent: 6668097 (2003-12-01), Hu et al.
patent: 6819796 (2004-11-01), Hong et al.
patent: 2004/0032906 (2004-02-01), Lillig
patent: 2005/0226506 (2005-10-01), Aharon et al.
patent: 2007/0031037 (2007-02-01), Blake et al.
patent: WO 2007/076890 (2007-07-01), None
patent: WO 2007/076891 (2007-07-01), None
patent: WO 2007/076892 (2007-07-01), None
patent: WO 2007/076893 (2007-07-01), None
Lucchese et al., “Color Image Segmentation: A State-of-the-Art Survey”, Proc. of the Indian National Science Academy (INSA-A), vol. 67, A, No. 2, pp. 207-221, (2001).
Kim et al.; “An edge-based Adaptive Morphology Algorithm for Image Noise Reduction”, Journal of the Korean Institute of Telematics & Electronics, Seoul, KR, vol. 34S, No. 3, pp. 84-96, (1997).
Volodymyr Kindratenko; “Image Processing Techniques”, Development and Application of Image Analysis Techniques for Identification and Classification of Microscopic Particles: Part 1 , PH.D. Thesis, http://www.ncsa.utac/edu/(kindr/phd/), pp. 1.1-1.56, (1997).
Cabrelli et al.; “Automatic Representation of Binary Images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Service Center, vol. 12, No. 12, pp. 1190-1196, (1990).
Nabout et al.; “A Novel Closed Contour Extractor, Principle and Algorithm”, IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, US, vol. 1, pp. 445-448, (1995).
Griesser; “Real-Time, GPU-based Foreground-Background Segmentation”, Technical Report 269, pp. 1-36, (2005).
Seitner et al.; “Pedestrian Tracking Based on Colour and Spatial Information”, Proceeding of the Digital Imaging Computing: Techniques and Applications (DICTA 2005), IEEE Computer Society, 8 pages, (2005).
Ikkjin et al.; “Image Processing on the GPU” University of Pennsylvania, GPU Programming and Architecture, pp. 1-7, (2005).
Feldmann et al.; “Real-Time Segmentation for Advanced Disparity Estimation in Immersive Videoconference Applications,” Proc. of WSCG 2002, 10thINT. Conference on Computer Graphics, Visualization and Computer Vision, vol. 10, No. 1, pp. 171-178, (2002).
Hanbury; “Circular Statistics Applied to Colour Images”, 8thComputer Vision Winter Workshop, 6 pages, (2003).
Lefevre et al.; “Multiresolution Color Image Segmentation Applied to Background Extraction in Outdoor Images”, RFAI Publication, IS&T European Conference on Color in Graphics, Image and Vision, Poitiers (France), pp. 1-9, ( 2002).
Luca Rossato et al.; “Segmentation of Video Sequences”, U.S. Appl. No. 12/087,269, filed Oct. 1, 2008.
Luca Rossato et al.; “Average Calculation in Color Space, Particularly for Segmentation of Video Sequences”, U.S. Appl. No. 12/087,265, filed Jun. 30, 2008.
Luca Rossato et al.; “Edge Comparison in Segmentation of Video Sequences”, U.S. Appl. No. 12/087,251, filed Jun. 27, 2008.
Luca Rossato et al.; “Edge-Guided Morphological Closing in Segmentation of Video Sequences”, U.S. Appl. No. 12/087,204, filed Aug. 18, 2008.
Bertolino et al.; “Detecting People in Videos for Their Immersion in a Virtual Space”; Proceedings of the 2ndInternational Symposium on Image and signal Processing and Analysis, in conjunction with the 23rdInternational Conference on Information Technology Interfaces, Univ. Zagreb, Zagreb, Croatia, pp. 313-318, (2001).
Jabri et al.; “Detection and Location of People in Video Images Using Adaptive Fusion of Color and Edge Information”, Pattern Recognition, Proceedings of the 15thInternational Conference, IEEE Comput. Soc., U.S., vol. 4, pp. 627-630, (2000).
Mureika et al.; “Multifractal Fingerprints in the Virtual Arts”; Leonardo, MIT Press, USA, vol. 37, No. 1, pp. 53-56, (2004).
Chien et al.; “Efficient Moving Object Segmentation Algorithm Using Background Registration Technique”; IEEE Transactions on circuits and systems for Video Technology, IEEE Service Center, vol. 12, No. 7, pp. 577-586, (2002).
Butler et al.; “Real-Time Adaptive Background Segmentation”, Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP-2003), pp. 349-352, (2003).
François et al., “Adaptive Color Background Modeling for Real-Time, Segmentation of Video Streams”, Proceedings of the International Conference on Imaging Science, Systems, and Technology, pp. 227-232, (1999).

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