US2011206251A1PendingUtilityA1

Method of characterizing an image source utilizing predetermined color spaces

41
Individually held — no corporate assignee on recordPriority: May 26, 2004Filed: Oct 25, 2010Published: Aug 25, 2011
Est. expiryMay 26, 2024(expired)· nominal 20-yr term from priority
Inventors:Thomas E. RamsayEugene B. RamsayGerard FelteauVictor HamiltonMartin RichardAnatoliy FesenkoOleksandr Andrushchenko
G06V 10/255
41
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Claims

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

exact text as granted — not AI-modified
1 . A method, comprising
 receiving a series of images; and   using a nonlinear transformation to map the series of images to at least one predetermined color space to yield at least one template with which a source of the images can be identified.   
     
     
         2 . The method of  claim 1 , wherein the series of images comprise a series of hyperspectral images. 
     
     
         3 . The method of  claim 1 , wherein the series of images comprise a series of satellite images. 
     
     
         4 . The method of  claim 1 , wherein the series of images comprise a series of infrared images. 
     
     
         5 . The method of  claim 1 , wherein the series of images comprise a series of laser radar images. 
     
     
         6 . The method of  claim 1 , wherein the series of images comprise a series of x-ray images and the source of the images comprises an x-ray imaging machine. 
     
     
         7 . The method of  claim 1 , wherein the series of images comprise a series of infrared images and the source of the images comprises a forward looking infrared (FLIR) system. 
     
     
         8 . The method of  claim 1 , wherein the series of images comprise a series of magnetic resonance images and the source of the images comprises a magnetic resonance imaging (MRI) machine. 
     
     
         9 . The method of  claim 1 , wherein the series of images comprise a series of positron emission tomography (PET) images and the source of the images comprises a PET machine. 
     
     
         10 . The method of  claim 1 , wherein the series of images comprise a series of laser radar images and the source of the images comprises a laser radar imaging system. 
     
     
         11 . The method of  claim 1 , wherein the source of the images comprises a camera. 
     
     
         12 . The method of  claim 11 , wherein the camera comprises a digital camera. 
     
     
         13 . The method of  claim 1 , wherein the series of images comprise a series of ultrasound images and the source of the images comprises an ultrasound imaging system. 
     
     
         14 . The method of  claim 1 , wherein the series of images comprise a series of ultrasound images. 
     
     
         15 . The method of  claim 1 , wherein the source of the images comprises a radar system. 
     
     
         16 . The method of  claim 1 , wherein the source of the images comprises a phased-array radar system. 
     
     
         17 . The method of  claim 1 , wherein the series of images comprise a series of medical images. 
     
     
         18 . The method of  claim 1 , wherein the series of images comprise a series of grey-scale images.

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