Image comparison, portrait comparison and face recognition are all image processing technologies, but their implementation methods and application scenarios are different.
- image comparison
Image comparison refers to the similarity comparison of two or more pictures through computer vision technology. It mainly includes steps such as image feature extraction, matching and evaluation, which are usually implemented using deep learning techniques such as neural networks.
Application scenarios: Image comparison can be applied to scenarios such as face recognition, item recognition, license plate recognition, etc. abnormal situation etc.
- Portrait comparison
Portrait comparison refers to the comparison and analysis of two or more portrait pictures to determine whether two or more face pictures are a product service of the same person. Technically, the service provided by face detection is required. The above similarity algorithm is used to judge the similarity. At present, it has also been developed to realize the comparison of video streams and pictures, as well as the comparison of facial signals from various sensors.
It should be noted that the face comparison technology cannot guarantee 100% accuracy. A threshold must be set on the product. If the similarity is above the threshold, we will judge that the face comparison has passed (that is, it is judged to be the same person).
Application scenarios: portrait comparison is mainly used in attendance machine to check in after entering the face picture, verifying whether it is the same person in face recognition, etc.
- face recognition
Face recognition is a technology that captures a face image through a camera and other equipment and compares it with the existing face information in the database. This is usually done using techniques such as artificial intelligence, computer vision and pattern recognition. Compared with traditional identity authentication methods, such as passwords and fingerprints, face recognition is more convenient and faster.
The technical process of the specific implementation of the principle of face recognition technology mainly includes the following four parts, namely, face image acquisition and preprocessing, face detection and feature extraction, portrait comparison and living body detection.
Compared with face comparison technology, face recognition has added the function of live detection, which can better judge that the user is a real person and can better defend against attacks such as videos and masks.
Application scenarios: Face recognition is widely used in access control systems, entry-exit management, public security security, user identity information judgment in financial credit scenarios, face recognition in game anti-addiction links and other fields.
As an API interface service provider, in order to meet the needs of different application scenarios, Databao provides portrait comparison interface, live detection, and face recognition, covering multiple usage scenarios such as APP, H5, and applets.
Databao links national ministries and commissions and state-owned enterprises with single-handed authorization to ensure data compliance from the source. Help network operators conduct identity verification more safely, quickly, and conveniently, and avoid identity fraud in the process of real-name authentication. Databao does not retain data to ensure the security of data interaction.