Systems and methods for classifying objects in digital images captured using mobile devices

  • US 9,311,531 B2
  • Filed: 03/13/2014
  • Issued: 04/12/2016
  • Est. Priority Date: 03/13/2013
  • Status: Active Grant
First Claim
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1. A method, comprising:

  • receiving or capturing a digital image using a mobile device;

    using a processor of the mobile device to;

    determine whether an object depicted in the digital image belongs to a particular object class among a plurality of object classes based on feature-space discrimination wherein the feature space discrimination utilizes one or more of support-vector-machine (SVM) techniques, transductive classification techniques, and maximum entropy discrimination (MED) techniques;

    determine one or more object features of the object based at least in part on the particular object class at least partially in response to determining the object belongs to the particular object class;

    build or select an extraction model based at least in part on the one or more determined object features; and

    extract data from the digital image using the extraction model, the extracting comprising detecting one or more lines of text in the object, and the detecting comprising;

    projecting the digital image onto a single dimension;

    projecting each color channel of the digital image onto a single channel along the single dimensiondetermining a distribution of light and dark areas along the projection;

    determining a plurality of dark pixel densities, each dark pixel density corresponding to a position along the projection;

    determining whether each dark pixel density is greater than a probable text line threshold; and

    designating each position as a text line upon determining the corresponding dark pixel density is greater than the probable text line threshold.

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