System and method for using a template in a predetermined color space that characterizes an image source
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.
1 . A method of using at least one template in at least one predetermined color space that characterizes an image source, comprising:
receiving at least one image from the image source;
mapping the at least one image to the at least one predetermined color space to yield at least one mapped image; and
comparing the at least one mapped image to the at least one template.
2 . The method of claim 1 , further comprising determining whether the image source is at variance based on the comparing step.
3 . The method of claim 2 , wherein the determining step comprises determining whether the image source is calibrated.
4 . The method of claim 1 , further comprising determining a level of variance of the image source based on the comparing step.
5 . The method of claim 1 , further comprising determining whether the image source has malfunctioned based on the comparing step.
6 . The method of claim 1 , wherein the at least one image comprises a hyperspectral image.
7 . The method of claim 1 , wherein the at least one image comprises a satellite image.
8 . The method of claim 1 , wherein the at least one image comprises an infrared image.
9 . The method of claim 1 , wherein the at least one image comprises a laser radar image.
10 . The method of claim 1 , wherein the at least one image comprises an x-ray image and the source of the image comprises an x-ray imaging machine.
11 . The method of claim 1 , wherein the least one image comprises an infrared image and the source of the image comprises a forward looking infrared (FLIR) system.
12 . The method of claim 1 , wherein the at least one image comprises a magnetic resonance image and the source of the image comprises a magnetic resonance imaging (MRI) machine.
13 . The method of claim 1 , wherein the at least one image comprises a positron emission tomography (PET) image and the source of the image comprises a PET machine.
14 . The method of claim 1 , wherein the at least one image comprises a laser radar image and the source of the at least one image comprises a laser radar imaging system.
15 . The method of claim 1 , wherein the source of the at least one image comprises a camera.
16 . The method of claim 15 , wherein the camera comprises a digital camera.
17 . The method of claim 1 , wherein the at least one image comprises an ultrasound image and the source of the at least one image comprises an ultrasound imaging system.
18 . The method of claim 1 , wherein the at least one image comprises an ultrasound image.
19 . The method of claim 1 , wherein the source of the at least one image comprises a radar system.
20 . The method of claim 1 , wherein the source of the at least one image comprises a phased-array radar system.
21 . The method of claim 1 , wherein the at least one image comprises a medical image.
22 . The method of claim 1 , further comprising normalizing the at least one image based on the comparing step.
23 . The method of claim 1 , wherein the at least one image comprises a grey-scale image.
24 . A method of using at least one template in at least one predetermined color space that characterizes an image source, comprising:
receiving a plurality of images from the image source;
mapping the plurality of images to the at least one predetermined color space to yield mapped images; and
comparing the mapped images to the at least one template.
25 . The method of claim 24 , further comprising normalizing the plurality of images based on the comparing step.
26 . The method of claim 24 , wherein the plurality of images comprise a plurality of grey-scale images.
27 . A method of using at least one template in at least one predetermined color space that characterizes an image source, comprising:
receiving an image from a different image source;
mapping the image to the at least one predetermined color space to yield a mapped image; and
comparing the mapped image to the at least one template.
28 . The method of claim 27 , further comprising determining whether the different image source and the image source are at variance based on the comparing step.
29 . The method of claim 28 , wherein the determining step comprises determining whether the image source and the different image source are calibrated with respect to each other.
30 . The method of claim 27 , further comprising determining a level of variance between the image source and the different image source based on the comparing step.
31 . The method of claim 27 , further comprising determining whether one of the image source and the different image source has malfunctioned based on the comparing step.
32 . A system for using at least one template in at least one predetermined color space that characterizes an image source, comprising:
an image receiving unit that receives at least one image from the image source;
an image mapping unit that maps the at least one image to the at least one predetermined color space to yield at least one mapped image; and
a comparing unit that compares the at least one mapped image to the at least one template.