Nowadays security is one of the most important challenges in the life of any modern human being. One of the means of providing security is through identification of people. To provide identification science of biometrics has been employed. Biometrics is a science that uses the behavioral and biological characteristics of a person to identify him. Fingerprint verification is an important biometric technique for personal identification. Most of the automatic verification systems are based on matching of fingerprint minutiae. Extraction of minutiae is an essential process in design of fingerprint verification systems. Estimation of orientation of the lines in an image is one of the complicated processes for enhancement of fingerprint and minutiae extraction. In this thesis, with improvement and implementation of existing algorithms a hardware scheme is presented which is based on a pipelined architecture in order to perform real-time orientation estimation. Most of the minutiae extraction methods use binarization to convert the grayscale image into a binary image. Recently a number of methods have been devised to extract the minutiae directly from the grayscale image. These routines require complex and time consuming computations and hence are performed through software. This complexity has hindered their hardware implementation. In this thesis a new approach is offered which significantly reduces the required computations and extracts the minutiae from the image with relatively high speed. Also, offered is a new architecture which implements the suggested method.