Face recognition technology solutions Provider
Face recognition technology refers to the use of computer technology for analysis and comparison to recognize faces. Face recognition is a popular computer technology research field, including face tracking and detection, automatic adjustment of image magnification, night infrared detection, automatic adjustment of exposure intensity and other technologies.
Face recognition technology belongs to biometric recognition technology, which distinguishes individual organisms from the biological characteristics of the organism (generally refers to people). Based on the original face recognition algorithm, the accuracy rate reached 98.52%, surpassing the human eye recognition capability (97.53%) for the first time.
Technology Introduction
Face recognition technology is based on human facial features. For the input face image or video stream, first determine whether there is a face. If there is a face, then further give the position, size and main points of each face. Location information of facial organs. Based on this information, the identity features contained in each face are further extracted and compared with known faces to identify the identity of each face.
The broad sense of face recognition actually includes a series of related technologies for building a face recognition system, including face image acquisition, face positioning, face recognition preprocessing, identity confirmation, and identity search, etc.; while the narrow sense of face recognition refers specifically to the adoption of A technology or system for confirming or finding the identity of a person's face.
The biological characteristics studied by the biometric recognition technology include face, fingerprint, palm print, iris, retina, voice (voice), body shape, personal habits (such as the strength and frequency of typing on the keyboard, signature), etc. The corresponding recognition technology has people Face recognition, fingerprint recognition, palmprint recognition, iris recognition, retina recognition, voice recognition (voice recognition can be used for identity recognition and voice content recognition, only the former belongs to biometric recognition technology), body shape recognition, keyboard percussion Identification, signature recognition, etc.
Technical Principle
Face recognition technology consists of three parts:
(1) Face detection: reference template method/face rule method/sample learning method/skin color model method/feature sub-face method
(2) Face tracking: Face tracking refers to dynamic target tracking of detected faces. Specifically, a model-based method or a method based on a combination of motion and model is adopted. In addition, using skin color model tracking is also a simple and effective method.
(3) Face comparison: feature vector method/face pattern template method
The core of face recognition technology is actually "local human body feature analysis" and "graphic/neural recognition algorithm". This algorithm is a method that uses the various organs and characteristic parts of the human face. For example, the identification parameters formed by multiple data corresponding to the geometric relationship are compared, judged and confirmed with all the original parameters in the database. Generally, the judgment time is less than 1 second.
Functional Module
Face capture and tracking function: Face capture refers to detecting a portrait in an image or a frame of a video stream, separating the portrait from the background, and automatically saving it. Portrait tracking refers to the use of portrait capture technology to automatically track a designated portrait when it moves within the range captured by the camera.
Face recognition comparison: There are two comparison modes for face recognition: verification and search. Verification is to compare the captured portrait or the designated portrait with a registered object in the database to verify whether it is the same person. Search-style comparison refers to searching for the existence of a designated portrait from all the portraits registered in the database.
Face modeling and retrieval: The registered portrait data can be modeled to extract the features of the face, and the generated face template (face feature file) can be saved in the database. When performing face search (search style), model the designated person, and then compare it with the template of all people in the database for recognition, and finally list the most similar people based on the compared similarity value List.
The real person identification function:The system can identify whether the person in front of the camera is a real person or a picture. In order to prevent users from using photos to falsify. This technology requires the user to perform facial expressions in coordination.
Image quality inspection: The quality of the image directly affects the recognition effect. The image quality inspection function can evaluate the image quality of the photos to be compared, and give corresponding suggested values to assist the recognition.
Analysis Algorithm
A regional feature analysis algorithm widely used in face recognition technology. It combines computer image processing technology with the principles of biostatistics. It uses computer image processing technology to extract facial feature points from videos and analyzes using the principles of biostatistics. Establish a mathematical model, that is, a facial feature template. Use the built face feature template and the face of the subject to perform feature analysis, and give a similar value based on the analysis result. This value can be used to determine whether it is the same person.
There are many methods of face recognition. The main face recognition methods are: geometric feature face recognition method / eigenface (PCA) based face recognition method / neural network face recognition method / elastic map matching face recognition Method/Line Segment Hausdorff Distance (LHD) Face Recognition Method/Support Vector Machine (SVM) Face Recognition Method.
Technical Details
Generally speaking, a face recognition system includes image capture, face positioning, image preprocessing, and face recognition (identity confirmation or identity search). The input of the system is generally one or a series of face images with undetermined identities, and several face images with known identities in the face database or corresponding codes, and the output is a series of similarity scores, indicating The identity of the face to be recognized.
Algorithms for face recognition can be classified as:
*Feature-based recognition algorithms
*Appearance-based recognition algorithms
*Template-based recognition algorithms
*Recognition algorithms using neural network
Advantages and Disadvantages
Advantages of face recognition: Compared with other biometric technologies: non-contact, the user does not need to directly contact the device; non-mandatory, the recognized face image information can be actively obtained; concurrency, that is, it can be used in actual application scenarios Sort, judge and recognize multiple faces.
Weaknesses of face recognition: sensitive to the surrounding light environment, which may affect the accuracy of recognition; human facial hair, accessories and other occlusions, facial aging and other factors, need to be compensated by artificial intelligence; Some of the key features of the software will be revised).
Technology application and application prospects
Biometric technology is widely used in government, military, banking, social welfare, e-commerce, security and defense and other fields.
1. Enterprise and residential security and management. Such as face recognition access control and attendance systems, face recognition anti-theft doors, etc.
2. Electronic passport and ID card.
3. Public security, justice and criminal investigation. Such as the use of facial recognition systems and networks to search for fugitives on a global scale.
4. self service. For example, the bank's automatic teller machine, if face recognition is also applied, it will avoid the phenomenon of cash being stolen by others.
5. information security. Such as computer login, e-government and e-commerce. In e-commerce, all transactions are completed online, and many approval procedures in e-government have also been moved online.
