Design and development of a security module with inbuilt neural network methodologies and an advanced technique on fingerprint recognition

Developing a security module with accurate, effective face recognition and fingerprint recognition is dealt in my paper. Personal safety and unique identification of a individual is necessary and it plays an vital role in certain situations where only the authorized persons can access the resources particularly in the secured storage of medicines, jewels, documentations, mines, militaries, laboratories, ATMs, ration shops, universities and places were harmful items were placed and dealt on it. Government organizations are nowadays investing huge money and looking for improving security systems in feedback with the recent terrorism that affects the country´s safety mechanism. Thus to prevent mishandling of secured data and misuse of it by unauthorized persons particularly hackers and anti social elements. My paper deals with the technology to prevent unauthorized usage of secured resources, ensuring unique identity and safety with the usage of fuzzy logic, and neural networks in implementing face recognition techniques and also an advanced technique on fingerprint recognition. Fingerprint recognition technique is used for allowing access only to the stored fingerprints, and my proposed system can be effectively utilized in the event of complete shut down or drained battery, thus retaining all stored fingerprints for cross verification with the data and access can be allowed. Face recognition technique is effectively used in place of failure of biometrie technology. Where, it is not applicable to non-consistent people, so incorporating neural algorithms thus enabling secure access. Effective face recognition methodologies and improved fingerprint recognition techniques are dealt in this paper with effectiveness.