Access Control Infrared Face Recognition Based On Gabor Wavelet Transform And PCA

In the process of infrared face recognition,feature extraction is an important part,because the extraction and processing of effective face information directly relates to the infrared face recognition rate.Feature extraction mainly includes global feature extraction and local feature extraction.Due to the principle of self-imaging,infrared face image has the problems of low resolution,blurred edge contours,and indistinct details.It has certain difficulty in the extraction of face features,and therefore affects the face recognition rate.In order to solve the above problems,this paper adopts the preprocessing technology,feature extraction method and segmentation technology of infrared face image to achieve the improvement and application of infrared face recognition rate.The face recognition algorithm based on K_L transform is discussed.The face recognition algorithm based on Gabor wavelet transform fusion PCA is used to realize the recognition of the infrared face of the access control.The paper mainly studies from the following aspects:1.Explore the principle and characteristics of infrared face image imaging and analyze factors affecting infrared face recognition.2.Improve the quality and clarity of the image by preprocessing(denoising and enhancing)the infrared face image.3.Using Canny operator to extract the image edge features,Gilles extract the marking features,Gabor wavelet transform to extract the local texture features,etc.to achieve the extraction of facial features of infrared face images.4.Using Otsu threshold segmentation and other technologies to achieve the segmentation of infrared face images.5.Realize the access control infrared face recognition and application based on Gabor wavelet transform fusion PCA.