Cluster Optimization for Angle Oriented Face Matching Using Bayes Condition

In the prevailing time, it is not easy to compare the input data sets and large database sets. Consequently, we must follow the inventive methods i.e., classification and statistical methods are applied on normal applications and also web based applications. As a result of this process relies on validation/verification, and it is more complex that needs very much importance. In this paper, we proposed an Angle Oriented Recognition Algorithm. In this algorithm, comparison is done between the database images to many input nested cluster images. The solution of this problem is applied through Fuzzy Clusters (namely Clock wise and Anti-clock wise directions) based on Angle Oriented Recognition using Bayes conditional probability. A high recognition rate is observed using software reliability testing to this approach and it is proved by an example.