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Method and apparatus for extracting feature points from digital image

  • US 8,306,366 B2
  • Filed: 08/22/2008
  • Issued: 11/06/2012
  • Est. Priority Date: 08/23/2007
  • Status: Active Grant
First Claim
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1. A method of extracting feature points from a digital image in a multiprocessor system using a scale invariant feature transform (SIFT) technique, the method comprising:

  • dividing an original image into a plurality of regions so as to be allocated to a plurality of processors of the multiprocessor system;

    performing, by the plurality of processors, blurring operations by levels;

    dividing the images blurred by levels into a plurality of regions to be allocated to the processors and calculating, by the plurality of processors, differences of Gaussian (DoGs); and

    generating feature point data according to the calculated DoGs, wherein;

    the performing of the blurring operations comprises;

    adding a predetermined number of virtual pixels to both borders of an original line to produce a revised line on which the blurring operation is to be performed;

    performing convolution operations on all pixels of the revised line using a blur kernel; and

    correcting a result value obtained from one of the convolution operations in which one or more of the virtual pixels is used for calculating the result value, and the correcting the result value comprises;

    generating a correction weight which indicates a ratio of a sum of kernel values applied to pixels other than the virtual pixels in the one of the convolution operations to the sum of all kernel values; and

    dividing the result value by the generated correction weight.

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