Feature Extraction Using Tipca Technique along with the Combination of K-nn Classifier

Face Recognition has becoming the most challenging and interesting area in all applications. It is one of the best biometric techniques. Feature Extraction is the major problem in face recognition. Researchers developed many best feature extraction techniques. The existing papers have followed SVM and KNN Algorithms. But since it requires more classification accuracy of the image, this paper shows how the Transform Invariant PCA technique provides better accuracy when used with K-Nearest Neighbor classifier. The experimental result shows the comparative analysis of the TIPCA algorithm with the combination of the KNN classifier algorithm.