An IOT Method for Reducing Classification Error in Face Recognition With the Commuted Concept of Conventional Algorithm

Abstract

The initial work has discussed the conventional approach of algorithms along with their drawbacks and features. Apart from that types of face recognition methodologies have been discussed with application of IOT trends. We specifically depicts a descriptive idea about working and applications of all conventional algorithms which have been commuted concept wise in proposed methodologies section of our work Our work consists of literature survey so we can provide a reason for the previous work and get basic ground for performing and implementing proposed work. One of a common procedures of face detection has been discussed that’s has been worked out in past with accuracy .The observation in this work leads to propose the method by commuting the conventional algorithm, Basically the work done with conventional approach has been discussed in this section with a strong focus over the role of Iot in face recognition and what is importance of Iot in this domain and what changes Iot concept has bring about as far as face recognition with different approach has been concerned . Not only PCA concept has been commuted but along with Pca, Svm, naïve bayes classifier, DCT, Gabor, neural network efficiency and their combined effect has been performed and analyzed later. Our work has been focusing around commuted concept of conventional algorithms so this particular chapter is very much important to discuss the conventional methodologies perform by classical mathematically implemented techniques for classifications. With the help of the analysis we will discuss the problem formulation and comparison of proposed work with existing work .So our work is basically about the problem existing with conventional algorithm for classifications and what lead us to propose the commuted concept further to deal or minimize the effect of that particular problem ,Our work is not primarily based on face recognition but to calculate the classification error through conventional algorithm and then compare it with our proposed commuted concept and combined effect of conventional algorithms as well, like PCA+SVM PCA+ Kernel SVM, Commuted Concept of PCA +Naïve bayes Classifier .We have gone through with different cases to ensure the minimization of classification error through proposed method .The goal of the work is to associate the application of