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Recent study on various surveillance systems has given us idea on research of soft biometrics which enables the recognition of unconstrained human faces. It also comprises of other methods where comparative soft biometrics will show the superior performance of recognition when compared to the categorical soft biometrics. It focuses on several studies which highlighted the ability of retrieval recognition of both unconstrained and constrained environments. These studies will only addresses face recognition on general attributes by raising question on the feasibility of generating the comparative labels form the facial images automatically. Facial recognition mainly divides the face into various sections for better recognizing the features of the face. If it matches with the database facial image that it will be unlocked automatically or else it will be locked when it doesn't find any features with the existing data. In this project we will be using LPBH algorithm for facial recognition which contains LFW dataset and HAAR classifier and it also include the Open CV for the efficiency of the attributes.