BIOMETRICS AUTHENTICATION BASED ON A NORMALIZED IMAGE OF AN OBJECT

• US 20180075291A1
• Filed: 03/02/2017
• Published: 03/15/2018
• Est. Priority Date: 09/12/2016
• Status: Abandoned Application

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: TIAN, Guifen, NONOGAKI, Nobuhiro
• Application Number:
  US15/448,553
• Publication Number:
  US 20180075291A1
• Time in Patent Office: Days
• CPC Class Codes: G06T 3/02 Affine transformations for image registration G06T3/147; for image mosaicing G06T3/4038
• CPC Class Codes: G06V 40/168 Feature extraction; Face representation
• CPC Class Codes: G06V 40/172 Classification, e.g. identification

Abstract

A method for carrying out a biometrics authentication includes detecting an object from a first image including the object, detecting feature points of the object in the detected object, generating a second image based on the feature points, wherein the second image is a normalized image of the object that is obtained by rotating and resizing the object in the first image, determining whether or not the object in the second image faces front, calculating a feature value of the object upon determining that the object in the normalized image faces front, and comparing the calculated feature value with a reference feature value for the biometrics authentication.

Claims

1. A method for carrying out a biometrics authentication, comprising:

detecting an object from a first image including the object;

detecting feature points of the object in the detected object;

generating a second image based on the feature points, wherein the second image is a normalized image of the object that is obtained by rotating and resizing the object in the first image;

determining whether or not the object in the second image faces front with predetermined size;

calculating a feature value of the object upon determining that the object in the normalized image faces front; and

comparing the calculated feature value with a reference feature value for the biometrics authentication.

2. The method according to claim 1, wherein determining whether or not the object in the second image faces front includes:

setting a region of interest in the second image, the region of interest including the feature points;

detecting a part of the object from the region of interest;

calculating a value for the detected part of the object, the value being greater when the detected part of the object faces front relative to when the detected part of the object faces an angled direction with respect to the front; and

determining whether or not the calculated value is greater than a threshold value, wherein the object is determined to face front when the calculated value is greater than the threshold value.

3. The method according to claim 2, wherein

the value correlates with a Joint-Haarlike feature value of the object in the second image, and increases as the Joint-Haarlike feature value increases.

4. The method according to claim 1, wherein determining whether or not the object in the second image faces front includes:

setting a plurality of regions of interest in the second image, each region of interest including at least one feature point;

detecting a part of the object from each of the regions of interest;

calculating a value for each of the detected parts of the object, the value being greater when the detected part of the object faces front relative to when the detected part of the object faces an angled direction with respect to the front;

calculating a total of the values; and

determining whether or not the calculated total is greater than a threshold value, wherein the object is determined to face front when the calculated total is greater than the threshold value.

5. The method according to claim 4, wherein

the value correlates with a Joint-Haarlike feature value of the object in the second image, and increases as the Joint-Haarlike feature value increases.

6. The method according to claim 1, wherein

the object is a human face, and

the feature points include points on each pupil, points on inner ends of eyebrows, points on inner ends of eyes, points on outer ends of the eyes, points on nostrils, a point on a nasal apex, points on mouth ends, and a point in a mouth.

7. The method according to claim 1, wherein

the feature value is one of a discrete cosine transform (DCT) feature value and a Gabor feature value.

8. A method for carrying out a biometrics authentication, comprising:

detecting an object from a first image including the object;

detecting a plurality of feature point candidates for each of feature points of the object in the detected object;

determining a plurality of groups of feature point candidates, each of which include one feature point candidate for each of the feature points;

generating a second image for each group of feature points candidates based on the feature points candidates in the group, wherein the second image is a normalized image of the object that is obtained by rotating and resizing the object in the first image;

determining whether or not the object in each of the second images faces front;

selecting one of the second images in which the object is determined to face front;

calculating a feature value of the object from the selected second image; and

comparing the calculated feature value with a reference feature value for the biometrics authentication.

9. The method according to claim 8, wherein determining whether or not the object in each of the second images faces front includes:

setting a region of interest in the second image, the region of interest including a group of the feature point candidates;

detecting a part of the object from the region of interest;

calculating a value for the detected part of the object, the value being greater when the detected part of the object faces front relative to when the detected part of the object faces an angled direction with respect to the front; and

determining whether or not the calculated value is greater than a threshold value, wherein the object is determined to face front when the calculated value is greater than the threshold value.

10. The method according to claim 9, wherein

the value correlates with a Joint-Haarlike feature value of the object in the second image, and increases as the Joint-Haarlike feature value increases.

11. The method according to claim 8, wherein determining whether or not the object in each of the second images faces front includes:

setting a plurality of regions of interest in the second image, each region of interest including at least one feature point candidate;

detecting a part of the object from each of the regions of interest;

calculating a value for each of the detected parts of the object, the value being greater when the detected part of the object faces front relative to when the detected part of the object faces an angled direction with respect to the front;

calculating a total of the values; and

determining whether or not the calculated total is greater than a threshold value, wherein the object is determined to face front when the calculated total is greater than the threshold value.

12. The method according to claim 11, wherein

the value correlates with a Joint-Haarlike feature value of the object in the second image, and increases as the Joint-Haarlike feature value increases.

13. The method according to claim 8, wherein

the object is a human face, and

the feature points include points on each pupil, points on inner ends of eyebrows, points on inner ends of eyes, points on outer ends of the eyes, points on nostrils, a point on a nasal apex, points on mouth ends, and a point in a mouth.

14. The method according to claim 8, wherein

the feature value is one of a discrete cosine transform (DCT) feature value and a Gabor feature value.

15. A non-transitory computer readable medium comprising a program that is executable in a computing device to cause the computing device system to perform a method for carrying out a biometrics authentication, the method comprising:

detecting an object from a first image including the object;

detecting feature points of the object in the detected object;

generating a second image based on the feature points, wherein the second image is a normalized image of the object that is obtained by rotating and resizing the object in the first image;

determining whether or not the object in the second image faces front;

calculating a feature value of the object upon determining that the object in the normalized image faces front; and

comparing the calculated feature value with a reference feature value for the biometrics authentication.

16. The non-transitory computer readable medium according to claim 15,

wherein determining whether or not the object in the second image faces front includes:

setting a region of interest in the second image, the region of interest including the feature points;

detecting a part of the object from the region of interest;

calculating a value for the detected part of the object, the value being greater when the detected part of the object faces front relative to when the detected part of the object faces an angled direction with respect to the front; and

determining whether or not the calculated value is greater than a threshold value, wherein the object is determined to face front when the calculated value is greater than the threshold value.

17. The non-transitory computer readable medium according to claim 16, wherein

the value correlates with a Joint-Haarlike feature value of the object in the second image, and increases as the Joint-Haarlike feature value increases.

18. The non-transitory computer readable medium according to claim 15,

wherein determining whether or not the object in the second image faces front includes:

setting a plurality of regions of interest in the second image, each region of interest including at least one feature point;

detecting a part of the object from each of the regions of interest;

calculating a value for each of the detected parts of the object, the value being greater when the detected part of the object faces front relative to when the detected part of the object faces an angled direction with respect to the front;

calculating a total of the values; and

determining whether or not the calculated total is greater than a threshold value, wherein the object is determined to face front when the calculated total is greater than the threshold value.

19. The non-transitory computer readable medium according to claim 18, wherein

the value correlates with a Joint-Haarlike feature value of the object in the second image, and increases as the Joint-Haarlike feature value increases.

20. The non-transitory computer readable medium according to claim 15, wherein

the object is a human face, and

the feature points include points on each pupil, points on inner ends of eyebrows, points on inner ends of eyes, points on outer ends of the eyes, points on nostrils, a point on a nasal apex, points on mouth ends, and a point in a mouth.