Face identification method applied to adaptive drive seat

Abstract

The invention provides a face identification method applied to an adaptive drive seat; the method comprises the following steps: loading a face identity characteristic head portrait database; building a face identification model, and training a loaded face identification database; obtaining a video image from a camera; using a cascade classifier to detect whether the video image contains face characteristic information or not; if yes, extracting the face portion, and forming a face image; carrying out dimension normalization for the extracted characteristic head portrait, and carrying out histogram equalization treatment; using two dimension discrete rapid Fourier transform to convert the face image from a space domain to a frequency domain, and extracting characteristics; comparing the extracted characteristics in the face identification database, if the similarity is higher than a preset threshold, a predicted ID label is outputted so as to confirm the passenger ID, thus starting the adaptive drive seat; asking to input the face identity if the similarity is smaller than the preset threshold. The face identification method is applied to an unmanned vehicle auxiliary driving system, and matched with the adaptive drive seat, thus fast and accurately carrying out face identification with high efficiency.

Description

technical field [0001] The invention relates to the field of face recognition and the field of vehicle auxiliary driving systems, in particular to a face recognition method applied to an adaptive driving seat. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. Use a camera or camera to collect images or video streams containing faces, and automatically detect and track faces in the images, and then perform a series of related image processing technologies on the detected faces, usually also called portrait recognition, face recognition, etc. identify. At present, the application of face recognition technology is becoming more and more common, but the face recognition technology in the existing technology still has technical defects, such as being greatly affected by the environment, easily deceived by photos, and not suitable for the natural changes of the face, resulting in insufficient rec...

AI Technical Summary

Problems solved by technology

At present, the application of face recognition technology is becoming more and more common, but the face recognition technology in the existing technology still has technical defects, such as being greatly affected by the environment, easily deceived by photos, and not suitable for the natural changes of the face, resulting in insufficient recognition rate. advanced questions

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