Optical topographic imaging

1. A method of studying a predefined portion of an object having a feature of interest and that is of a class of objects that each have a substantially similar optical property, the method comprising:

activating each of a plurality of light sources to directly illuminate the object, wherein each of the plurality of light sources provides illumination from a different illumination direction and wherein the plurality of light sources is maintained in a stable configuration relative to the object;

for each illumination direction, generating an image from light scattered from the object with a camera maintained in a stable configuration relative to the plurality of light sources; and

applying a methodology derived from machine learning for the class of objects to:

filter the generated images for each illumination direction for a characteristic consistent with the feature of interest;

determine surface gradients for the object from the filtered images for each illumination direction taking into account a system geometry defining each said illumination direction, wherein determining the surface gradients comprises extracting the surface gradients through application of periodic factors generated as a function of a geometry defined by positions of the plurality of light sources relative to the object; and

integrate the surface gradients to generate a topography of a surface of the predefined portion of the object.

2. The method recited in claim 1 further comprising determining an albedo of the surface of the object from the generated images.

3. The method recited in claim 1 wherein:

the predefined portion of the object is approximately planar; and

filtering the generated images comprises applying a band-pass filter to the generated images.

4. The method recited in claim 1 wherein:

the feature of interest comprises an orientation; and

filtering the generated images comprises applying an orientation filter to the generated images.

5. The method recited in claim 1 wherein:

the feature of interest comprises a chromatic characteristic; and

filtering the generated images comprises applying a chromatic filter to the generated images.

6. The method recited in claim 1 wherein determining the surface gradients comprises applying a deconvolution to the generated images to account for anisotropic scattering of light by a bulk component of the object.

7. The method recited in claim 1 wherein the topography of the surface of the object is defined by a topographic image, the method further comprising applying a transformation to the topographic image.

8. The method recited in claim 7 wherein the transformation changes a contrast of the topographic image.

9. The method recited in claim 7 wherein the transformation reduces artifacts due to specular light within the topographic image.

10. The method recited in claim 7 wherein the transformation binarizes the topographic image.

11. The method recited in claim 1 wherein the light sources are substantially monochromatic light sources.

12. The method recited in claim 11 wherein each of the light sources generates light at substantially the same wavelength.

13. The method recited in claim 1 wherein the light sources are distributed about the object at substantially the same elevation and are distributed substantially uniformly in azimuth relative to the object.

14. The method recited in claim 1 wherein portions of the object are in optical contact with a platen that is substantially transparent to light generated by the light sources.

15. The method recited in claim 1 wherein:

the light sources provide light at a plurality of wavelengths; and

determining the surface gradients for the object comprises determining surface gradients for the object at each of the plurality of wavelengths.

16. The method recited in claim 15 wherein at least some of the light sources comprise polychromatic light sources.

17. The method recited in claim 15 further comprising:

determining an albedo of the surface of the object from the generated images at each of the plurality of wavelengths; and

comparing the determined albedo at the plurality of wavelengths to determine an authenticity of the object as a biometric sample.

18. The method recited in claim 1 wherein the object comprises a biometric sample.

19. The method recited in claim 1 wherein the object comprises a machined barcode.

20. The method recited in claim 1 wherein directly illuminating the object with the plurality of light comprises sequentially activating the light sources.

21. The method recited in claim 1 wherein activating each of the plurality of light sources comprises simultaneously activating at least some of the plurality of light sources in a pattern to determine a response to individual light sources with a transform.

22. The method recited in claim 1 wherein determining surface gradients for the object from the generated images comprises regionally modifying at least one of the generated images to exclude a shadowed portion of the object.

23. A device for studying a predefined portion of an object having a feature of interest and that is of a class of objects that each have a similar optical property, the device comprising:

a plurality of light sources disposed to provide illumination of the object from different illumination directions, wherein the plurality of light sources is maintained in a stable configuration relative to the object;

a camera disposed to receive light scattered from the object, wherein the camera is maintained in a stable configuration relative to the plurality of light sources; and

a computational unit in communication with the plurality of light sources and with the camera, the computational unit having:

instructions to activate the light sources to directly illuminate the object;

instructions to operate the camera in concert with activation of the light sources to generate an images of the object for each of the illumination directions; and instructions to apply a methodology derived from machine learning for the class of objects to:

filter the generated images for each illumination direction for a characteristic consistent with the feature of interest;

determine surface gradients for the object from the filtered images for each illumination direction taking into account a system geometry defining each said illumination direction, wherein determining the surface gradients comprises extracting the surface gradients through application of periodic factors generated as a function of a geometry defined by positions of the plurality of light sources relative to the object; and

integrate the surface gradients to generate a topography of a surface of the predefined portion of the object.