Providing loyalty discounts to customers in retail stores

Abstract

This paper describes the study of different types of algorithms being commonly used for face recognition. We will use the algorithm that yields better accuracy to detect potential customers purchasing in a retail store and accordingly providing discounts based on their loyalty.. In recent times discounts to customers are provided in terms of sale or as a general discounts but there is no scope of discounts based on loyalty or trust that customers show on their purchase irrespective of any age group. Thus the set of all faces in the feature space is treated as a high-dimensional vector space. The faces of different subjects as being in different classes for all subjects in the training set, we establish a framework for performing a cluster separation analysis in the feature space. Also, having labeled all instances in the training set and having defined all the classes, we compute the within and between-class scatter matrices. The most commonly and used mechanism for face detection is Eigen faces algorithm but however we will go through a couple of other algorithms in order to determine better accuracy in face recognition which will our prime goal. Then we will use Fisher's LDA mechanism in order to classify the buyer's as high, mid and low potential groups and accordingly take decision based on that. Hence it can overcome the problem of varying illumination. It is used to extract the magnitude of edge information and it works well even during the variations in poses and the illumination conditions. HOG works well under such challenging situations as it represents directionality of edge information thereby making it significant for the study of pattern and structure of the interested object.