IP Library › Granted Patent US 11,842,567
Granted Patent B2
US 11,842,567 · App. 17/360,323 · Granted Dec 12, 2023

Information processing apparatus, genetic information generation method and program

Inventors: Hisashi Hagiwara (Tokyo, JP); Noritada Yasumoro (Tokyo, JP); Yoshinori Mishina (Tokyo, JP)
Assignee: NEC CORPORATION
G06V40/171G06F16/535G06F16/55G06T1/00G06T7/00G06T7/0012G06V40/165G06T2207/30004G06T2207/30201
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Quick Facts
Patent No.
US 11,842,567
App. No.
17/360,323
Granted
Dec 12, 2023
Kind
B2
Abstract

An information processing apparatus comprises an extraction part and a genetic information generation part. The extraction part extracts a phenotypic site(s) representing a genetic phenotype(s) of a living entity from the image. The genetic information generation part generates genetic information of the living entity captured in the image based on the phenotypic site(s) extracted by the extraction part. The image comprises a person image in which a person captured. The genetic information generation part may generate genetic information of the person captured in the person image.

Claims (49)

1. An information processing apparatus, comprising a processor and a memory storing program instructions executable by the processor, wherein the processor is configured to:

extract one or more of phenotypic sites representing one or more genetic phenotypes of a living entity from an image, and

output an emphasized-image in which the phenotypic sites are emphasized, wherein

the image is a person image in which a person is captured,

the processor is configured to determine phenotypes represented in the phenotypic sites so as to generate genetic information on the phenotypes of the person, and

the processor is configured to execute the image processing to the phenotypic sites by pattern matching so as to determine the phenotypes represented in the phenotypic sites.

2. The information processing apparatus according to claim 1 , wherein the processor is configured to

determine whether each of the phenotypes represented in the phenotypic sites is a dominant trait or a recessive trait.

3. The information processing apparatus according to claim 2 , wherein the processor is configured to

comparer a biological sample information including genetic phenotypes of a biological sample with a determination result so as to determine whether a person providing the biological sample is identical with the person captured in the person image, and

generate genetic information including an identity-determination result.

4. The information processing apparatus according to claim 1 , wherein

the memory is configured to store a phenotypic site list in which the phenotypic sites to be extracted are described, and

the processor is configured to execute image processing on the person image so as to extract the phenotypic sites described in the phenotypic site list.

5. The information processing apparatus according to claim 3 , wherein the processor is configured to determine whether the person providing the biological sample is identical with the person captured in the person image using weights applied to each of the phenotypic sites or each of the phenotypes.

6. The information processing apparatus according to claim 5 , wherein

the weights applied to each of the phenotypic sites or each of the phenotypes are configured to be changeable.

7. A genetic information generation method, comprising:

extracting one or more of phenotypic sites representing one or more genetic phenotypes of a living entity from an image, and

outputting an emphasized-image in which the phenotypic sites are emphasized, wherein

the image is a person image in which a person is captured,

the method further comprises determining phenotypes represented in the phenotypic sites so as to generate genetic information on the phenotypes of the person, and

the method further comprises executing the image processing to the phenotypic sites by pattern matching so as to determine the phenotypes represented in the phenotypic sites.

8. The genetic information generation method according to claim 7 , wherein the method further comprises determining whether each of the phenotypes represented in the phenotypic sites is a dominant trait or a recessive trait.

9. The genetic information generation method according to claim 8 , wherein the method further comprises

comparing a biological sample information including genetic phenotypes of a biological sample with a determination result so as to determine whether a person providing the biological sample is identical with the person captured in the person image, and

generating genetic information including an identity-determination result.

10. The genetic information generation method according to claim 7 , wherein the method further comprises

storing a phenotypic site list in which the phenotypic sites to be extracted are described, and

executing image processing on the person image so as to extract the phenotypic sites described in the phenotypic site list.

11. The genetic information generation method according to claim 9 , wherein the method further comprises determining whether the person providing the biological sample is identical with the person captured in the person image using weights applied to each of the phenotypic sites or each of the phenotypes.

12. The genetic information generation method according to claim 11 , wherein

the weights applied to each of the phenotypic sites or each of the phenotypes are configured to be changeable.

13. A non-transitory computer readable recording medium storing therein a program causing a computer to execute processing comprising:

extracting one or more of phenotypic sites representing one or more genetic phenotypes of a living entity from an image, and

outputting an emphasized-image in which the phenotypic sites are emphasized, wherein

the image is a person image in which a person is captured,

the program further causing the computer to execute processing comprising determining phenotypes represented in the phenotypic sites so as to generate genetic information on the phenotypes of the person, and

the program further causing the computer to execute processing comprising executing the image processing to the phenotypic sites by pattern matching so as to determine the phenotypes represented in the phenotypic sites.

14. The non-transitory computer readable recording medium according to claim 13 , wherein the program further causing the computer to execute processing comprising: determining whether each of the phenotypes represented in the phenotypic sites is a dominant trait or a recessive trait.

15. The non-transitory computer readable recording medium according to claim 14 , wherein the program further causing the computer to execute processing comprising:

comparing a biological sample information including genetic phenotypes of a biological sample with a determination result so as to determine whether a person providing the biological sample is identical with the person captured in the person image, and

generating genetic information including an identity-determination result.

16. The non-transitory computer readable recording medium according to claim 13 , wherein the program further causing the computer to execute processing comprising

storing a phenotypic site list in which the phenotypic sites to be extracted are described, and

executing image processing on the person image so as to extract the phenotypic sites described in the phenotypic site list.

17. The non-transitory computer readable recording medium according to claim 15 , wherein the program further causing the computer to execute processing comprising determining whether the person providing the biological sample is identical with the person captured in the person image using weights applied to each of the phenotypic sites or each of the phenotypes.

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

the weights applied to each of the phenotypic sites or each of the phenotypes are configured to be changeable.

Priority Claims (1)
JP 2016-240559 · Dec 12, 2016 · national
Continuity (2)
Continuation 16468568
Related Publication 20210326577A1 · Oct 21, 2021
Cited By (1)
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