Human face detection and recognition play important roles in many applications such as video surveillance and face image database management. In our project, we have studied worked on both face detection and recognition techniques and developed algorithms for them. In face detection we followed two techniques which are termed as ‘Feature based approach’ and ‘skin color segmentation approach’. Also we developed algorithms for both the approaches. The feature based approach was used to detect the faces in grey images where multiple faces were detected. In skin color segmentation approach we also extracted the face from multiple faces or objects using the average face color. For the face recognition we used the algorithm of eigenface system based on the algorithm PCA (principal component analysis) in which we recognize an unknown test image by comparing it with the known training images stored in the database as well as give information regarding the person recognized. These techniques works well under robust conditions like complex background, different face positions. These algorithms gave different rates of accuracy under different conditions as experimentally observed. We have taken real life examples and simulated the algorithms in MATLAB successfully.