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Feature extraction using pixel-level and object-level analysis

  • US 7,933,451 B2
  • Filed: 11/13/2006
  • Issued: 04/26/2011
  • Est. Priority Date: 11/23/2005
  • Status: Active Grant
First Claim
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1. In a graphical information system (GIS), a method for processing a digital image depicting one or more physical objects to locate a feature in the digital image, the method comprising the following:

  • by a processor, executing a pixel-level cue algorithm to identify an interesting area of a raster image depicting the one or more physical objects;

    determining a pixel-level probability that the interesting area of the raster image identified is the feature using a result from the pixel-level cue algorithm;

    comparing the pixel-level probability to a pixel-level cue threshold; and

    if the pixel-level probability satisfies the pixel-level cue threshold;

    converting at least a portion of the raster image to a vector layer by geometric modeling using points, lines, curves, and polygons to generate a representation of digital vector objects represented by the points, lines, curves and polygons;

    executing an object-level cue algorithm on the vector layer to identify an interesting area of the vector layer;

    determining an object-level probability that the interesting area of the vector layer is the feature using a result of the pixel-level cue algorithm; and

    comparing the object-level probability to an object-level threshold.

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