System and method for identifying objects of interest in image data
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 identifying an object of interest in image data, comprising:
receiving the image data; and
applying at least one divergence transform to the image data to effect divergence of the object of interest from other objects.
2 . The method of claim 1 , wherein the at least one divergence transform comprises a series of divergence transforms.
3 . The method of claim 1 , wherein the at least one divergence transform comprises at least one point operation.
4 . The method of claim 3 , wherein the at least one point operation is at least partially a non-linear point operation.
5 . The method of claim 3 , wherein the at least one point operation comprises at least one nodal point.
6 . The method of claim 5 , wherein the at least one nodal point is adjusted so as to effect the divergence of the object of interest from other objects.
7 . The method of claim 1 , wherein the at least one divergence transform is adapted to maintain an integrity of the object of interest during divergence of the object of interest from other objects.
8 . The method of claim 1 , further comprising generating an output image containing the object of interest.
9 . The method of claim 8 , wherein the object of interest is distinguished from other objects in the output image by adjusting a visual parameter of the object of interest and other objects based on the results of the at least one divergence transform.
10 . The method of claim 9 , wherein the visual parameter comprises color.
11 . The method of claim 9 , wherein the visual parameter comprises luminance.
12 . The method of claim 1 , wherein the image data comprises nonparametric image data.
13 . The method of claim 1 , wherein the image data comprises two-dimensional image data.
14 . The method of claim 1 , wherein the image data comprises three-dimensional image data.
15 . The method of claim 1 , wherein the image data comprises x-ray image data.
16 . A method of identifying an object of interest in image data, comprising:
receiving the image data;
segmenting the image data to identify object candidates;
applying at least one divergence transform to original image pixels that correspond to the object candidates to effect divergence of the object of interest from other objects; and
identifying the object of interest based on its response to the at least one divergence transform.
17 . The method of claim 16 , wherein the image data is segmented based on color, density and/or atomic weight characteristics.
18 . The method of claim 16 , wherein the at least one divergence transform comprises at least one point operation.
19 . The method of claim 18 , wherein the at least one point operation comprises at least one nodal point that is adjusted so as to effect the divergence of the object of interest from other objects.
20 . A system for identifying an object of interest in image data, comprising:
an input channel for receiving the image data;
an image analysis system for applying at least one divergence transform to the received image data to yield transformed image data in which the object of interest diverges from other objects; and
a display for displaying an output image from the transformed image data.
21 . The system of claim 20 , wherein the at least one divergence transform comprises at least one point operation.
22 . The system of claim 21 , wherein the at least one point operation comprises at least one nodal point that is positioned so as to effect the divergence of the object of interest from other objects in the transformed image data.
23 . A method of identifying an object of interest in image data, comprising:
receiving the image data; and
applying a series of divergence transforms to the image data to effect divergence of the object of interest from other objects.
24 . The method of claim 23 , wherein each divergence transform in the series of divergence transforms comprises at least one point operation.
25 . The method of claim 24 , wherein the at least one point operation comprises at least one nodal point that is adjusted so as to effect the divergence of the object of interest from other objects.
26 . A system for identifying an object of interest in image data, comprising:
an input channel for receiving the image data;
an image analysis system for applying a series of divergence transforms to the received image data to yield transformed image data in which the object of interest diverges from other objects; and
a display for displaying an output image from the transformed image data.
27 . The system of claim 26 , wherein each divergence transform in the series of divergence transforms comprises at least one point operation.
28 . The system of claim 27 , wherein the at least one point operation comprises at least one nodal point that is adjusted so as to effect the divergence of the object of interest from other objects.