METHOD AND SYSTEM FOR IMAGE IDENTIFICATION AND IDENTIFICATION RESULT OUTPUT

• US 20100278436A1
• Filed: 07/30/2009
• Published: 11/04/2010
• Est. Priority Date: 04/30/2009
• Status: Active Grant

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Lin, Yu-Ting, Chang, Chun-Lung, Wu, Tung-Chuan, Huang, Kuo-Tang, Tsai, Ya-Hui
• Granted Patent: US 8,391,560 B2
• Time in Patent Office: Days
• US Class Current: 382/209
• CPC Class Codes: G06V 20/625 License plates
• CPC Class Codes: G06V 20/63 Scene text, e.g. street names

Abstract

The present invention provides a method and a system for image identification and identification result output, which determines a location coordinate with respect to an image and a rotating angle based on at least one direction of the image according to features of the image. The image is compared to a plurality of sample images stored in a database according to the rotating angle so as to obtain at least one identification result. By means of the method and the system of the present invention, identification can be achieved with respect to various rotating angles and distances so as to improve the identification rate.

Claims

1. A method for image identification and identification result output, comprising steps of:

providing an image to be identified comprising a region of interest thereon;

acquiring a feature in the region of interest;

determining a rotating angle based on at least one direction according to the feature; and

comparing the image with sample images in a database corresponding to the rotating angle to obtain at least one identification result.

2. The method for image identification and identification result output as recited in claim 1, wherein the step of determining the rotating angle further comprises steps of:

determining a standard image comprising a standard feature region;

performing a calculation on the feature in the region of interest and the standard feature region so as to obtain a location corresponding to the standard feature region in the region of interest; and

determining the rotating angle of the region of interest according to the location.

3. The method for image identification and identification result output as recited in claim 2, wherein the calculation is based on geometric matching.

4. The method for image identification and identification result output as recited in claim 1, wherein the rotating angle is based on a first direction and is within a range between ±

60 degrees.

5. The method for image identification and identification result output as recited in claim 1, wherein the rotating angle is based on a second direction and is within a range between ±

60 degrees.

6. The method for image identification and identification result output as recited in claim 1, further comprising a step of determining a scale relation between the region of interest and the sample images according to the feature.

7. The method for image identification and identification result output as recited in claim 1, wherein the region of interest comprises identification information.

8. The method for image identification and identification result output as recited in claim 1, wherein the feature further comprises contrast, greyscale, chrominance or spectrum on the boundary of identification information.

9. The method for image identification and identification result output as recited in claim 1, wherein the feature further comprises contrast, greyscale, chrominance or spectrum on the boundary of the region of interest.

10. The method for image identification and identification result output as recited in claim 1, wherein the region of interest is formed by the boundary of a license plate on a carrier.

11. The method for image identification and identification result output as recited in claim 1, wherein the step of comparing further comprises steps of:

acquiring a feature image from the region of interest;

acquiring the sample images in the database according to the at least one rotating angle, each sample image having respectively a standard image region and at least one non-standard image region, wherein the standard image region has pixels corresponding to a first feature value respectively, and the non-standard image region has pixels corresponding to a second feature value respectively;

performing a normalized correlation matching calculation on a third feature value of each pixel in the feature image and the first feature value or the second feature value corresponding to each pixel in the plurality of sample images to obtain a similarity index of the feature image corresponding to the plurality of sample images respectively;

collecting a plurality of similarity indexes with respect to the feature image compared with the plurality of sample images; and

sorting the plurality of similarity indexes and outputting at least one of comparison results.

12. The method for image identification and identification result output as recited in claim 11, wherein the first feature value and the second feature value are respectively a combination of a weight value and a greyscale value, and the third feature value is a greyscale value.

13. The method for image identification and identification result output as recited in claim 11, wherein normalized correlation matching is performed by dividing the product of the weight value corresponding to each pixel in the sample image, the difference between the greyscale value of each pixel and the average greyscale value in the sample image, and the difference between the greyscale value of each pixel and the average greyscale value in the feature image by the product of the standard deviation of the greyscale value of the sample image and the standard deviation of the greyscale value of the feature image.

14. The method for image identification and identification result output as recited in claim 11, wherein the step of acquiring the sample images further comprises steps of:

determining the size of the sample images;

providing in each of the sample images the standard image region

providing in each of the sample images the non-standard image region;

storing the sample images in the database;

observing the identification result after a plurality times of training; and

modifying the standard image region and the non-standard image region in the sample images

15. The method for image identification and identification result output as recited in claim 14, wherein the non-standard image region is formed by providing a pixel with the first feature value and the second feature value in the standard image region according to mis-identified characters in the standard image region.

16. A system for image identification and identification result output, comprising:

a database capable of providing a plurality of sample images;

an image acquiring unit capable of acquiring an image;

a feature acquiring unit capable of acquiring all features in the region of interest on the image;

an operation and processing unit capable of determining a rotating angle based on at least one direction in the region of interest according to the feature and comparing an identification information image with the sample images corresponding to the rotating angle in the database to obtain at least one identification result; and

an identification and output unit being electrically connected to the operation and processing unit to output at least one identification result.

17. The system for image identification and identification result output as recited in claim 16, wherein the operation and processing unit further comprises an enhancing unit capable of enhancing the image.

18. The system for image identification and identification result output as recited in claim 16, wherein the angle is determined by geometric matching.

19. The system for image identification and identification result output as recited in claim 16, wherein the rotating angle based on a first direction is within a range between ±

60 degrees.

20. The system for image identification and identification result output as recited in claim 16, wherein the rotating angle based on a second direction is within a range between ±

60 degrees.

21. The system for image identification and identification result output as recited in claim 16, wherein each sample image has respectively a standard image region and at least one non-standard image region, wherein the standard image region has pixels corresponding to a first feature value respectively, and the non-standard image region has pixels corresponding to a second feature value respectively.

22. The system for image identification and identification result output as recited in claim 21, wherein the non-standard image region is formed by providing a pixel with the first feature value and the second feature value in the standard image region according to mis-identified characters in the standard image region.

23. The system for image identification and identification result output as recited in claim 16, wherein the operation and processing unit excludes images of impossible characters or digits according to a relative location of the feature image in the identification mark when each feature image is compared with the plurality of sample images stored in the database by the operation and processing unit.

24. The system for image identification and identification result output as recited in claim 16, wherein a normalized correlation matching calculation is performed on a third feature value of each pixel in the feature image and the first feature value or the second feature value corresponding to each pixel in the plurality of sample images to obtain a similarity index of the feature image corresponding to the plurality of sample images respectively.

25. The system for image identification and identification result output as recited in claim 16, wherein the region of interest comprises identification information.

26. The system for image identification and identification result output as recited in claim 25, wherein the feature further comprises contrast, greyscale, chrominance or spectrum on the boundary of identification information.

27. The system for image identification and identification result output as recited in claim 16, wherein the feature further comprises contrast, greyscale, chrominance or spectrum on the boundary of the region of interest.

28. The system for image identification and identification result output as recited in claim 16, wherein the operation and processing unit determines the scale relation between the size of the region of interest and the sample image according to the feature.