IMAGE IDENTIFICATION

• US 20090316993A1
• Filed: 12/06/2007
• Published: 12/24/2009
• Est. Priority Date: 01/10/2007
• Status: Abandoned Application

• Current Assignee: Mitsubishi Electric Corporation
• Original Assignee: Mitsubishi Electric Corporation
• Inventors: Brasnett, Paul, Bober, Miroslaw
• Application Number:
  US12/522,669
• Publication Number:
  US 20090316993A1
• Time in Patent Office: Days
• US Class Current: 382/190
• CPC Class Codes: G06V 10/48 by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation

Abstract

A method and apparatus for deriving a representation of an image by processing signals corresponding to the image is described. The method includes deriving a two-dimensional function (T(d, θ)), such as a Trace transform of the image, and decomposing, for instance by sub-sampling, the two-dimensional function (T(d, θ)) in at least one of its two dimensions, to obtain a reduced resolution Trace transform. The decomposed, two dimensional function is then used to derive the representation of the image.

Claims

1. A method of deriving a representation of an image by processing signals corresponding to the image using one or more processors, the method comprising:

processing the image, or a two dimensional function of the image, using a processor to obtain a two dimensional function of the image at reduced resolution; and

deriving, using a processor, the representation of the image using the reduced resolution two dimensional function of the image.

2. A method as claimed claim 1, wherein the step of processing the image, or a two dimensional function of the image, comprises

sub-sampling values for the image over predetermined intervals of at least one parameter of the two dimensional function of the image.

3. A method as claimed in claim 2, wherein the sub sampling comprises:

performing a statistical calculation, preferably summation or integration, on values for the image or function of the image, over predetermined intervals of at least one parameter of the image or two dimensional function of the image.

4. A method as claimed in claim 1, wherein the step of processing comprises processing the image using a set of lines in the image.

5. A method is claimed in claim 4, wherein the sets of lines correspond to one or more of:

stripes defined by an interval of a first parameter of the two dimensional function of the image and double cones defined by an interval of a second parameter of the two dimensional function of the image.

6. A method as claimed in claim 4, wherein the processing comprises applying a functional over the set of lines to derive the reduced resolution two dimensional function of the image.

7. A method as claimed in claim 1, wherein the step of processing comprises processing a two dimensional function of the image by sub-sampling values of the two dimensional function of the image over predetermined intervals of a first dimension thereof, to reduce the resolution of the two dimensional function of the image in the first dimension.

8. A method is claimed in claim 1, wherein the step of processing comprises processing a two dimensional function of the image by sub-sampling values of the two dimensional function of the image over predetermined intervals in a second dimension thereof, to reduce the resolution of the two dimensional function of the image in the second dimension.

9. A method as claimed in claim 7, wherein the two dimensional function of the image comprises a Trace transform of the image derived by applying a functional over all lines of the image, the two dimensional function defining values for the image in a Trace domain having distance and angle parameters.

10. A method as claimed in claim 1, wherein the step of using the reduced resolution two dimensional function of the image, to derive the representation of the image, comprises deriving a one-dimensional function of the image.

11. A method as claimed in claim 1, further comprising:

deriving a further function of the image, wherein the further function of a translated, scaled or rotated version of the image is a translated or scaled version of the further function of the image.

12. A method as claimed in claim 10 or claim 11, wherein the one dimensional function or further function is a circus function, or a function derived from a circus function.

13. A method as claimed in claim 10, wherein the step of using the reduced resolution two dimensional function of the image to derive the representation of the image comprises:

using a plurality of frequency components of a frequency representation of the one dimensional function or further function to derive a representation of the image.

14. A method as claimed in claim 13, wherein the frequency components are determined using a Fourier transform or a Haar transform.

15. A method as claimed in claim 13 or claim 14, wherein the representation of the image is derived using the steps of:

calculating the magnitude, or logarithm of the magnitude, of a plurality of frequency coefficients, and determining a difference between the magnitude, or logarithm of the magnitude, of each coefficient and its subsequent coefficient.

16. A method as claimed in claim 15, further comprising:

applying a threshold to each determined difference to derive a series of binary values, wherein applying the threshold provides a binary value of 0 if a said difference is less than zero, and a binary value of 1 if a said difference is greater than or equal to zero.

17. A method as claimed in claim 16, wherein the image representation comprises the binary values defined by the magnitudes, or logarithm of magnitudes, of the plurality of frequency components.

18. A method as claimed in claim 1, wherein the method comprises deriving multiple representations of the image, by performing the step of processing over a range of different widths for said intervals, and combining the multiple representations to generate a multi-resolution representation.

19. A method as claimed in claim 18, wherein said different interval widths are at least a factor of two different from each other.

20. A method of identifying an image comprising:

deriving a representation of the image using a method as claimed claim 1, and associating the representation with the image.

21. A method of comparing images comprising comparing representations of each image derived using the method of claim 1.

22. A method as claimed in claim 21, wherein the comparison comprises determining a Hamming distance.

23. A method as claimed in claim 21 or claim 22, comprising selecting images based on comparisons of representations.

25. An apparatus for deriving a representation of an image, the apparatus comprising:

a memory storing images or descriptors of images; and

a processor configured to execute the method of claim 1.

26. A computer-readable medium comprising instructions that, when executed, cause one or more processors to perform the method of claim 1.

24. (canceled)