SYSTEM AND METHOD FOR DETERMINING WHETHER THERE IS AN ANOMALY IN DATA

• US 20090010521A1
• Filed: 01/14/2008
• Published: 01/08/2009
• Est. Priority Date: 05/26/2004
• Status: Active Grant

• Current Assignee: Applied Visual Sciences, Inc.
• Original Assignee: Applied Visual Sciences, Inc.
• Inventors: Andrushchenko, Oleksandr, Fesenko, Anatoliy, Ramsay, Thomas E., Ramsay, Eugene B., Hamilton, Victor, Richard, Martin, Felteau, Gerard
• Granted Patent: US 7,840,048 B2
• Time in Patent Office: Days
• US Class Current: 382/141
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes

Abstract

A system and method for identifying objects of interest in image data is provided. The present invention utilizes principles of Iterative Transformational Divergence in which objects in images, when subjected to special transformations, will exhibit radically different responses based on the physical, chemical, or numerical properties of the object or its representation (such as images), combined with machine learning capabilities. Using the system and methods of the present invention, certain objects that appear indistinguishable from other objects to the eye or computer recognition systems, or are otherwise almost identical, generate radically different and statistically significant differences in the image describers (metrics) that can be easily measured.

Claims

1. A method for determining whether there is an anomaly in data, comprising:

performing one of applying a divergence transform to the data, mapping the data to a predetermined color space and mapping the data to a feature space to yield altered data; and

comparing the altered data with a template of altered data created from a set of data not containing the anomaly to determine whether there is a difference between the altered data and the template, said difference corresponding to said anomaly.

2. The method of claim 1, further comprising repeating the performing and comparing steps using a different one of the applying and mapping steps if the comparing step does not produce a difference corresponding to the anomaly.