In today's networked world, the necessity of maintaining information safety as well as preserving the physical property is gradually becoming significant and tedious. As the requirement of high level of security arises, face recognition technology is bound to bend, to cope with the upcoming needs. Also, face recognition has caught the eye of researchers in the areas ranging from image processing and security to computer vision. Streams including content retrieval, network security and video compression get profited by face recognition technology. This is because face recognition deals with people as its centre of attention, thereby increasing the user-friendliness in human-computer interaction. It could also maintain our privacy and protect our assets without dropping our identity. But in this real world environment it seems to be a difficult task because of image variance in terms of position, size, expression and pose. In order to handle all these inter and intra-class variations in face images, various methodologies have been proposed. Here we analyse some methods, their possible strongholds and drawbacks.