Image recognition system and method using holistic Harr-like feature matching

1 . A method of image matching a test image to a template image, the method comprising:

extracting features from a test image, wherein the extracted features are Harr-like features extracted from key points in the test image;

matching extracted features from the test image with features from a template image;

transforming the test image according to matched extracted features; and

providing match results.

2 . The method of claim 1 , wherein matching extracted features from the test image with features from a template image comprises performing a holistic feature matching operation such that features are similar in terms of Harr quantities and have consistent spatial configurations.

3 . The method of claim 2 , wherein the matching extracted features from the test image with features from a template image utilizes a formula to define good match points (g), where the formula is

g

=

exp

⁡

(

-

d

σ

-

f

γ

)

where f is mean squared Harr and d is mean squared spatial differences.

4 . The method of claim 1 , wherein the template image and the test image have illumination differences.

5 . The method of claim 1 , wherein the template image and the test image have intra-class variation.

6 . The method of claim 1 , wherein the template image and the test image have scaling and varying view angles.

7 . The method of claim 1 , wherein the template image and the test image have occlusion and clutter backgrounds.

8 . The method of claim 1 , wherein the Harr-like features comprise a set of distinctive and invariant Harr-like description features.

9 . The method of claim 1 , wherein matching extracted features from the test image with features from a template image comprises selecting coherent points which are best match pairs from noisy feature points.

10 . A device having programmed instructions for image recognition between a test image and stored template images, the device comprising:

an interface configured to receive a test image;

an extractor configured to extract features from the test image, wherein the extracted features are Harr-like features extracted from key points in the test image; and

instructions that perform a matching operation where extracted features from the test image are matched with features from a template image to generate match results.

11 . The device of claim 10 , wherein the matching operation compares Harr quantities and spatial configurations of the features.

12 . The device of claim 10 , wherein the matching operation utilizes a formula to define good match points (g), where the formula is

g

=

exp

⁡

(

-

d

σ

-

f

γ

)

where f is mean squared Harr and d is mean squared spatial differences.

13 . The device of claim 10 , wherein the template image and the test image have illumination differences.

14 . The device of claim 10 , wherein the template image and the test image have intra-class variation.

15 . The device of claim 10 , wherein the matching operation selects coherent points which are best match pairs.

16 . The device of claim 15 , wherein the best match pairs are from noisy feature points.

17 . The device of claim 10 , wherein the device is selected from the group consisting of a mobile device, a robot and a computing device.

18 . A system for image recognition, the system comprising:

a pre-processing component that performs image normalization on a test image;

a feature extraction component that extracts Harr-like features from the test image, wherein the Harr-like features are from key points in the test image;

a matching component that matches features extracted from the test image with features from a template image; and

an image transformation component that performs transformation operations on the test image.

19 . The system of claim 18 , wherein the matching component tests features based on Harr quantities and spatial configurations.

20 . The system of claim 18 , wherein the matching component selects coherent points from the test image and the template image which are best match pairs.

21 . The system of claim 20 , wherein the best match pairs are from noisy feature points.

22 . The system of claim 18 , wherein the transformation operations performed by the image transformation component comprises any one of cropping, scaling, rotation, and non-linear deformation.

23 . The system of claim 18 , further comprising a feature processing component that selects and merges feature data from the test image.

24 . A software program, embodied in a computer-readable medium, for image matching a test image to a template image, comprising:

code for extracting features from a test image, wherein the extracted features are Harr-like features extracted from key points in the test image;

code for matching extracted features from the test image with features from a template image;

code for transforming the test image according to matched extracted features; and

code for providing match results.

25 . The software program of claim 24 , wherein the code for matching extracted features from the test image with features from a template image comprises code for performing a holistic feature matching operation such that features are similar in terms of Harr quantities and have consistent spatial configurations.

26 . A system for image matching a test image to a template image, the method comprising:

means for performing image normalization on a test image;

means for extracting Harr-like features from the test image, wherein the Harr-like features are from key points in the test image;

means for matching features extracted from the test image with features from a template image; and

means for performing transformation operations on the test image.

27 . The system of claim 26 , wherein the matching means tests features based on Harr quantities and spatial configurations.