Auther Check
The simplify is better!
We build a new generation human biometric authentication platform that is easy to integrate into existing applications, services or hardware products. We've designed an easy-to-use REST API so integration will go smoothly!
For liveness detection and anti-spoofing, we've developed Auther Embedded.
Overview
This page describes the technical requirements that must be met to start using facial recognition technology in your applications and products. Please read all the sections in detail and strictly follow the requirements specified in the documentation and your integration will go quickly and smoothly. Sign-up and get a free plan for testing!
Quick start guide
To send your first request, follow the steps below. For faster and more convenient testing, we recommend using Postman. Sign-up and get the API Key to authorize your requests.
- Check out the used terms in the glossary
- Prepare face image that meet image requirements
- Encode prepared image into Base64
- All http requests should be sent as a JSON format
- Get API Key in the dashboard to authorize your requests
- Insert the API Key into the request header
Glossary
List of terms that are used in requests and responses:
- api_key - authentication token for API access
- signing_key - RSA 2048 encryption public key
- person_id - identifier assigned by the client for each stored face
- faceImage - the input Base64-encoded image
- request_id - unique transaction identifier
- timestamp - current timestamp with milliseconds
- code - error message
- message - human readable error description
- created - date and time when person_id was created
- updated - date and time when person_id was updated
- sourceImage - the input Base64-encoded image
- targetImage - the input Base64-encoded image
- similarityThreshold - the minimum level of confidence in the face matches
- facesMatched - similarity level of confidence that the faces match (from 0 to 100)
- confidence - the confidence level that the selected images contain a face (from 0 to 100)
Image requirements
The input image as base64-encoded bytes is required. For successful preparation of the Bade64-encoded image, before you sent requests, follow to the next criteria:
- Prepare an image with a customer face in JPG/JPEG/PNG format
- Image size should be no more than 30 kb
- Face size on the image should be more than 80 pixels
- Encode the image for additional Base64 format
- Base64-encoded image must contain less than 400 000 characters
Image verification criteria
To successfully create a person_id, the image of the person you submit for enrollment will be verified for compliance with the following criteria:
- Face size
- Face blurity
- Face position
- Face lighting check
- One face on the image
- The similar face doesn't enrolled
Requests
All API requests must be sent in JSON format with the header:
Api-Key: api_key
{
"code": "F_001",
"type": "string",
"message": "string"
}
Authorization
Every request sent must be authenticated using the API Key. It should be sent in an HTTP header. You can create and manage your API Keys in the back-office. To get the API Key, you need to Sign-up and get a free plan for testing.
Required credentials
Base URL
Request headers
Response headers
Create person
To register a person in the system, please submit a Base64-encoded image of a a person on where the person looks straight ahead and also prepare the person_id you want to assign to this person in advance. When preparing the reference image, follow the requirements described above in the Image requirements section.
Request headers
Go to request headersRequest Body
{
"faceImage": "string"
}
Response headers
Go to response headersStatus code 200
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
Status code 400
{
"code": "string",
"message": "string"
}
Codes and messages for response 400
Update person
To update the data of a person in the system, please submit a Base64-encoded image of a a person on where the person looks straight ahead and also indicate the person_id of the person you want to assign new data to.
For preparing the reference image, follow the requirements described above in the Image requirements section.
Request headers
Go to request headersRequest Body
{
"faceImage": "base64format_string"
}
Response headers
Go to response headersStatus code 200
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
Status code 400
{
"code": "string",
"message": "string"
}
Codes and messages for response 400
HTTP Status code: 404
{
"code": "NF_001",
"message": "Face not found in collection"
}
Codes and messages for response 404
HTTP Status code: 401, 403, 500
Remove person
To remove a person's data from the system, just send the person_id parameter. The person's data will be deleted and the person_id will also be deleted.
Request headers
Go to request headersRequest Body
Response headers
Go to response headersHTTP Status code: 200
HTTP Status code: 400
{
"code": "string",
"message": "string"
}
Codes and messages for response 400
HTTP Status code: 404
{
"code": "NF_001",
"message": "Face not found in collection"
Codes and messages for response 404
HTTP Status codes: 401, 403, 500
Get person [beta]
To check if the person_id already exist in the system, just specify the path with person_id . If the person_id exist in response you will get the same person_id and information when person was created and updated.
Request headers
Go to request headersRequest Body
Response headers
Go to response headersHTTP Status code: 200
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
HTTP Status code: 400
{
"code": "string",
"message": "string"
}
Codes and messages for response 400
HTTP Status code: 404
{
"code": "NF_001",
"message": "Face not found in collection"
Codes and messages for response 404
HTTP Status codes: 401, 403, 500
Identify person
Submit the Base64-encoded image. With this request, we start 1:N searching for the most similar enrolled person in our system. The search result will be person_id, which matches the searched one by 98%.
To improve the quality and speed of recognition, follow the image requirements for the submitted images.
Request headers
Go to request headersRequest Body
{
"faceImage": "string"
}
Response headers
Go to response headersHTTP Status code: 200
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
HTTP Status code: 400
{
"code": "string",
"message": "string"
}
Codes and messages for response 400
HTTP Status code: 410
{
"code": "string",
"message": "string"
}
Codes and messages for response 410
HTTP Status codes: 401, 403, 500
Verify person [beta]
Comparison of the face of a person who declares that his face belongs to the known person_id. With this request, we start 1:1 matching for the enrolled person in our system. If the submitted person's face matches to 80% with the person's image that belongs to the declared person_id, then the verification result is successful.
Request headers
Go to request headersRequest Body
{
"faceImage": "string"
}
Response headers
Go to response headersHTTP Status code: 200
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
HTTP Status code: 400
{
"code": "R_002",
"message": "Request body exception"
}
Codes and messages for response 400
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
HTTP Status code: 404
{
"code": "R_002",
"message": "Request body exception"
}
Codes and messages for response 404
HTTP Status codes: 401, 403, 500
Compare person [beta]
Compares the face on the sourceImage with the largest face detected on the targetImage.
By default, the submitted sourceImage will be compared the targetImage with the 80% of similarity threshold. If you want to compare images with a custom similarity threshold (for example, 98%), specify this number in the request body [option]. In response, you get the similarity value of the facesMatched images.
Request headers
Go to request headersRequest Body
{
"targetImage": "string",
"sourceImage": "string"
}
Request Body [option]
{
"targetImage": "string",
"sourceImage": "string",
"similarityThreshold": number
}
Response headers
Go to response headersHTTP Status code: 200
{
"facesMatched": number
}
HTTP Status code: 400
{
"code": "R_002",
"message": "Request body exception"
}
Codes and messages for response 400
Response status codes
The custom 200 and 400 response codes are listed in the description for each request. Common server response codes are listed below.
HTTP Status code: 200
{
"personId": "string",
"created": "2020-09-03T16:05:08.938Z",
"updated": "2020-09-04T16:05:08.938Z"
}
HTTP Status code: 400
{
"code": "string",
"message": "string"
}
HTTP Status code: 401
{
"code": "string",
"message": "string"
}
HTTP Status code: 403
{
"code": "string",
"message": "string"
}
HTTP Status code: 404
{
"code": "string",
"message": "string"
}
HTTP Status code: 500
{
"code": "string",
"message": "string"
}
ENTERPRISE ONLY
Double encryption RSA-2048
This section describes how to use SHA-256 hashing and optional RSA-2048 encryption to sign requests. In this way, you can improve the security of data transmission. This option is available only for enterprise clients.
Signing with RSA-2048 [enterprise only]
This section describes how to use SHA-256 hashing and optional RSA-2048 encryption to sign requests. In this way, you can improve the security of data transmission. This option is available only for enterprise clients.
Required credentials
Base URL
Request headers
Response headers
Build request signature [enterprise only]
To create a request signature using hashing and encryption, follow the step-by-step instructions below:
- Form a line for request signature
- Hash the resulting value using SHA-256
- Encrypt the obtained hashing result with signing_key
- Encode the obtained encryption result with signing_key to Base64 format
- Now add the following headers to the request:
- Api-key
- Signature
- Timestamp
Verify response signature [enterprise only]
To decrypt the request signature using hashing and encryption, follow the step-by-step instructions below:
- Getting a hash from response signature
- Decode the Signature header value using Base64
- Decrypt the Base64 decoding result with signing_key
- Remember the decrypted result (hash#1)
- Getting a hash for comparison
- Form a line for response signature
- Hash the resulting value with SHA-256 (hash#2)
- Compare the hash you received (hash#1) with the decrypted value (hash#2) of the response signature header:
