The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 19, 2013

Filed:

Apr. 05, 2010
Applicants:

Hemanth Kumar Sangappa, Bangalore, IN;

Suresh Kirthi Kumaraswamy, Bangalore, IN;

Puneeth B Chandrashekhar, Bangalore, IN;

Inventors:

Hemanth Kumar Sangappa, Bangalore, IN;

Suresh Kirthi Kumaraswamy, Bangalore, IN;

Puneeth B Chandrashekhar, Bangalore, IN;

Assignee:

MindTree Limited, Bangalore, IN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06K 9/66 (2006.01);
U.S. Cl.
CPC ...
Abstract

A computer implemented method and system for detecting interest sections in a still image are provided. One or more sub images of the still image is subjected to segmentation. A gray scale version of interest sub images and/or a binary image version of the interest sub images are matched with a predefined template for filtering the interest sub images. Multiple prospective image sections comprising one or more of prospective interest sections and prospective near interest sections are determined by performing discriminative feature analyses of the filtered interest sub images using a gabor feature filter. The discriminative feature analyses are processed by a boosted cascade of classifiers. The boosted cascade of classifiers detects the interest sections in the still image from the prospective interest sections and the prospective near interest sections. The detected interest sections are subjected to a support vector machine classifier for further detecting interest sections.


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