The process of face recognition

The process of face recognition is face image acquisition and detection, key point extraction, face regularization (image processing), face feature extraction and face recognition comparison.

Face detection is mainly used for the preprocessing of face recognition, i.e., to accurately calibrate the position and size of the face in the image. The features available for face recognition system are usually categorized into visual features, pixel statistical features, face image transform coefficient features and face image algebraic features. Face feature extraction is based on certain features of the face, and face feature extraction, also known as face signatures, is the process of feature modeling of the face.

Face image preprocessing is based on the results of face detection, image processing, and ultimately serves the feature extraction process. Due to various conditions and random interference, the raw images obtained by the system often cannot be used directly. They must be used directly in the early stages of image processing. For face images, the preprocessing process mainly consists of light compensation, grayscale transformation, histogram equalization, composition, geometric correction, filtering and sharpening on grayscale.

Face Recognition Technology Features

Traditional face recognition technology is mainly based on visible light images of face recognition, which is also familiar to people's recognition methods, has more than 30 years of research and development history. However, this approach has insurmountable defects, especially when the environmental lighting changes, the recognition effect will be sharply reduced, and can not meet the needs of the actual system. The solution to the problem of illumination has three-dimensional image face recognition, and thermal imaging face recognition. However, these two technologies are still far from mature, and the recognition effect is not satisfactory.

Users do not need to specialize with the face acquisition equipment, almost in an unconscious state can be obtained face images, so that the sampling method is not mandatory. Users do not need to be in direct contact with the device to obtain face images, and in practical application scenarios can be multiple face sorting, judgment and recognition.