Design And Implementation Of Face Recognition System Platform Based On PCA Algorithm And FPGA

The face recognition is a forward subject in the computer vision domain which has great theoretical significance and practical value,and it is hot topic in the field of pattern recognition.The thesis analysis the traditional PCA algorithm,it proposes an improved algorithm,and implements the application on FPGA.This thesis introduces the design process of face recognition algorithm which is implemented by PCA.Firstly,the PCA technology and image processing technology are introduced.Based on this,the image preprocessing was introduced which consists of two parts: image enhancement and image segmentation operation.Through the image preprocessing,the face area can be obtained.Based on the description of the image pretreatment process,the thesis describes the work process of traditional face recognition algorithm based on PCA,the algorithm only use the feature of the face,when the number of features is less,the recognition rate is very low.In order to improve the face recognition rate,this thesis improves the face recognition algorithm.The features of eyes,mouth and nose is read from face feature region,and it been integrate to the whole face feature vector.The distances between feature vectors as the basis for face recognition.After improving the algorithm,the algorithm is implemented and tested.On this basis,the application of face recognition algorithm in FPGA is studied.At present,the face recognition algorithm based on PCA is implemented by MATLAB,the LBP part of face recognition algorithm is processed by FPGA,and the contrast test is carried out.The results show that the improved face recognition algorithm can improve the recognition rate effectively.