Types of Analyses and What They Check
Here, you'll get acquainted with types of analyses that Oz API provides and will learn how to interpret the output.
Using Oz API, you can perform one of the following analyses:
Each of the analyses has its threshold that determines the output of these analyses. By default, the threshold for all analyses is 0.5 or 50%.
- Biometry: if the final score is 0.5 / 50% or more, the faces on the analyzed media are considered similar.
- Blacklist: if the final score is 0.5 / 50% or more, the face on the analyzed media matches with one of the faces in the database.
- Quality: if the final score is 0.5 / 50% or more, the result is interpreted as an attack.
For more information on how to read the numbers in analyses' results, please refer to Quantitative Results.
The Biometry algorithm allows comparing several media and check if the people on them are the same person or not. As sources, you can use images, videos, and scans of documents (with photo). To perform the analysis, the algorithm requires at least two media (for details, please refer to Rules of Assigning Analyses).
After comparison, the algorithm provides a number that represents the similarity level. The number varies from 100 to 0% (1 to 0), where:
- 100% (1) – faces are similar, media represent the same person,
- 0% (0) – faces are not similar and belong to different people
The Liveness detection (Quality) algorithm aims to check whether a person in a video is a real human acting in good faith, not a fake of any kind.
The Best Shot algorithm checks for the best shot from a video (a best-quality frame where the face is seen the most properly). It is an addition to liveness.
After checking, the analysis shows the chance of a spoofing attack in percents.
- 100% (1) – an attack is detected, the person in the video is not a real living person,
- 0% (0) – a person in the video is a real living person.
*Spoofing in biometry is a kind of scam when a person disguises as another person using both program and non-program tools like deepfake, masks, ready-made photos, or fake videos.
The Documents analysis aims to recognize the document and check if its fields are correct according to its type.
Oz API uses a third-party OCR analysis service provided by our partner. If you want to change this service to another one, please contact us.
As an output, you'll get a list of document fields with recognition results for each field and a result of checking that can be:
- The documents passed the check successfully,
- The documents failed to pass the check.
Additionally, the result of Biometry check is displayed.
The Blacklist checking algorithm is used to determine whether the person on a photo or video is present in the database of pre-uploaded images. This base can be used as a blacklist or whitelist. In the former case, the person's face is being compared with the faces of known swindlers; in the latter case, it might be a list of VIPs.
After comparison, the algorithm provides a number that represents the similarity level. The number varies from 100 to 0% (1 to 0), where:
- 100% (1) – the person in an image or video matches with someone in the blacklist,
- 0% (0) – the person is not found in the blacklist.
Last modified 2mo ago