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:
Jun. 28, 2011

Filed:

Nov. 30, 2006
Applicants:

Amir Zahavi, Petach Tikva, IL;

Shai Nissim, Tel Aviv, IL;

Inventors:

Amir Zahavi, Petach Tikva, IL;

Shai Nissim, Tel Aviv, IL;

Assignee:

Other;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/46 (2006.01); G06K 9/66 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
Abstract

The invention is a method of using Wavelet Transformation and Artificial Neural Network (ANN) systems for automatic detecting and classifying objects. To train the system in object recognition different images, which usually contain desired objects alongside other objects are used. These objects may appear at different angles. Different characteristics regarding the objects are extracted from the images and stored in a data bank. The system then determines the extent to which each inserted characteristic will be useful in future recognition and determines its relative weight. After the initial insertion of data, the operator tests the system with a set of new images, some of which contain the class objects and some of which contain similar and/or dissimilar objects of different classification. The system learns from the images containing similar objects of different classes as well as from the images containing the class objects, since each specific class characteristic needs to be set apart from other class characteristic. The system may be tested and trained again and again until the operator is satisfied with the system's success rate of object recognition and classification.


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