Facial recognition is used in biometric technology. Facial recognition is the process of using the face to recognize or verify a person's identity. It captures, analyses, and compares patterns based on a person's facial details. The task of authenticating or identifying human faces from multimedia photos is accomplished using facial recognition technology. Viola and Jones present a method capable of accurately and quickly detecting faces in images. This technology can be used to accurately detect the facial features. Face tracking technology provides better opportunities for security and surveillance. This increases the level of protection. For example, facial tracking software helps improve surveillance strategies and serves as a basis for identifying terrorists and criminals. National borders, casinos, museums, banks or prisons are other examples where this system can be used for security. This paper proposes a face detection and eye and smile recognition system with real time images, using the Haar Cascade classifier for face, eye and smile recognition. This trace is based on the jpeg/jpg file format and can be acquired from any type of camera. It works with almost all types of image formats. Its classifier will detect facial features. In this research paper a comparison is also analyzed between face and facial detection by a camera captured image and saved images. Analysis of both types of code is also being made in this research work. The document also gives the percentage of accuracy by comparing the results. Therefore, this work aims at face processing with eye and smile detection. In this article it first detects the face using a web camera and then the captured image is processed and, on the image, it detects the face, eyes and smile.