Collation of Face Recognition Techniques: Image Registration and Dimension Reduction Approaches

Faces must be present in images for intelligent vision-based human computer interaction to work. Since many years ago, face recognition research has been ongoing and significant. This procedure entails facial tracking, expression recognition, and many other things. It is crucial to first register the positions of the photos in this process. However, maintaining such a database is highly challenging because of pose invariance, illumination invariance, shift invariance, scale and noise invariance. The Image Registration Algorithm will be used to register all of the unknown photos that are currently in the database. With the use of a reference, this registration technique tries to align a pattern image. This algorithm will produce features that are independent of translation, scaling and rotation. High dimension space, which must be decreased using a dimension reduction algorithm, is the primary challenge in face recognition. This low dimension subspace can be produced using dimension reduction methods like as Linear Discriminant Analysis, Principal Component Analysis and Locality Preserving Projection. In order to find the needed image from the given database, this study will first minimize the dimensions of every image that is now there.