METHOD AND APPARATUS FOR OBTAINING AND PROCESSING IMAGE FEATURES

• US 20090161967A1
• Filed: 12/20/2007
• Published: 06/25/2009
• Est. Priority Date: 12/20/2007
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Wang, Tao, Li, Jianguo, Zhang, Yimin
• Granted Patent: US 8,509,538 B2
• Time in Patent Office: Days
• US Class Current: 382/210
• CPC Class Codes: G06F 18/21 Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
• CPC Class Codes: G06F 18/217 Validation; Performance evaluation; Active pattern learning techniques
• CPC Class Codes: G06V 10/449 Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
• CPC Class Codes: G06V 10/70 using pattern recognition or machine learning optical pattern recognition or electronic computations therefor G06V10/88
• CPC Class Codes: G06V 10/776 Validation; Performance evaluation
• CPC Class Codes: G06V 40/165 using facial parts and geometric relationships

Abstract

Machine-readable media, methods, apparatus and system for obtaining and processing image features are described. In some embodiments, a Gabor representation of an image may be obtained by using a Gabor filter. A region may be determined from the Gabor representation, wherein the region comprises a plurality of Gabor pixels of the Gabor representation; and, a sub-region may be determined from the region, wherein the sub-region comprises more than one of the plurality of Gabor pixels. Then, a Gabor feature may be calculated based upon a magnitude calculation related to the sub-region and the region.

Claims

1. A method, comprising:

obtaining a Gabor representation of an image by using a Gabor filter;

determining a region from the Gabor representation, wherein the region comprises a plurality of Gabor pixels of the Gabor representation;

determining a sub-region from the region, wherein the sub-region comprises more than one of the plurality of Gabor pixels; and

calculating a Gabor feature based upon a magnitude calculation related to the sub-region and the region.

2. The method of claim 1, further comprising obtaining an integral image from the Gabor representation, wherein an integral pixel of the integral image corresponds to a Gabor pixel of the Gabor representation and value of the integral pixel is obtained by integrating magnitudes for Gabor pixels within a field defined by the Gabor pixel corresponding to the integral pixel.

3. The method of claim 2, further comprising performing the magnitude calculation related to the sub-region and the region based upon the integral image.

4. The method of claim 1, wherein the sub-region is determined with reference to one or more Haar patterns.

5. The method of claim 1, wherein the sub-region is determined with reference to one or more extended Haar patterns.

6. The method of claim 1, wherein the calculating the Gabor feature further comprises:

calculating a first magnitude sum for Gabor pixels within the sub-region;

calculating a second magnitude sum for Gabor pixels within the region; and

obtaining the Gabor feature by dividing the first magnitude sum by the second magnitude sum.

7. The method of claim 1, wherein the calculating the Gabor feature further comprises:

calculating a first magnitude sum for Gabor pixels within the sub-region;

calculating a second magnitude sum for Gabor pixels within a part of the region that does not overlap with the sub-region; and

obtaining the Gabor feature by subtracting the second magnitude sum from the first magnitude sum.

8. An apparatus, comprising:

a Gabor filter to obtain a Gabor representation of an image;

a region logic to determine a region from the Gabor representation, wherein the region comprises a plurality of Gabor pixels of the Gabor representation;

a sub-region logic to determine a sub-region from the region, wherein the sub-region comprises more than one of the plurality of Gabor pixels; and

a feature calculating logic to calculate a Gabor feature based upon a magnitude calculation related to the sub-region and the region.

9. The apparatus of claim 8, further comprising an integral logic to obtain an integral image from the Gabor representation, wherein an integral pixel of the integral image corresponds to a Gabor pixel of the Gabor representation, and value of the integral pixel is obtained by integrating magnitudes for Gabor pixels within a field defined by the Gabor pixel corresponding to the integral pixel.

10. The apparatus of claim 9, wherein the feature calculating logic is further to perform the magnitude calculation related to the sub-region and the region based upon the integral image.

11. The apparatus of claim 8, wherein the sub-region is determined with reference to one or more Haar patterns.

12. The apparatus of claim 8, wherein the sub-region is determined with reference to one or more extended Haar patterns.

13. The apparatus of claim 8, wherein the feature calculating logic is further to:

calculate a first magnitude sum for Gabor pixels within the sub-region;

calculate a second magnitude sum for Gabor pixels within the region; and

obtain the Gabor feature by dividing the first magnitude sum by the second magnitude sum.

14. The apparatus of claim 8, wherein the feature calculating logic is further to:

calculate a first magnitude sum for Gabor pixels within the sub-region;

calculate a second magnitude sum for Gabor pixels within a part of the region that does not overlap with the sub-region; and

obtain the Gabor feature by subtracting the second magnitude sum from the first magnitude sum.

20. The system of claim 13, wherein the plurality of instructions that cause the system calculating the Gabor feature, further cause the system to perform operations comprising:

calculating a first magnitude sum for Gabor pixels within the sub-region;

calculating a second magnitude sum for Gabor pixels within the region; and

obtaining the Gabor feature by dividing the first magnitude sum by the second magnitude sum.

15. A system, comprising:

a processor;

a machine-readable medium coupled to the processor, wherein the machine-readable medium further comprises a plurality of instructions which, if executed by the processor, cause the system to perform operations comprising;

obtaining a Gabor representation of an image by using a Gabor filter;

determining a region from the Gabor representation, wherein the region comprises a plurality of Gabor pixels of the Gabor representation;

determining a sub-region from the region, wherein the sub-region comprises more than one of the plurality of Gabor pixels; and

calculating a Gabor feature based upon a magnitude calculation related to the sub-region and the region.

16. The system of claim 15, wherein the plurality of instructions further cause the system to perform operations comprising:

obtaining an integral image from the Gabor representation, wherein an integral pixel of the integral image corresponds to a Gabor pixel of the Gabor representation, and value of the integral pixel is obtained by integrating magnitudes for Gabor pixels within a field defined by the Gabor pixel corresponding to the integral pixel.

17. The system of claim 16, wherein the plurality of instructions further cause the system to perform operations comprising:

performing the magnitude calculation related to the sub-region and the region based upon the integral image.

18. The system of claim 15, wherein the sub-region is determined with reference to one or more Haar patterns.

19. The system of claim 15, wherein the sub-region is determined with reference to one or more extended Haar patterns.