Mathematical Models Using Artificial Intelligence for Surveillance Systems

7Application of Fuzzy Approximation Method in Pattern Recognition Using Deep Learning Neural Networks and Artificial Intelligence for Surveillance

M. Geethalakshmi¹*, Sriram V.² and Vakkalagadda Drishti Rao²

¹Department of Mathematics, KCG College of Technology, Karapakkam, Chennai, Tamil Nadu, India

²Department of Computer Science, KCG College of Technology, Karapakkam, Chennai, Tamil Nadu, India

Abstract

This paper deals with the idea of image processing techniques in surveillance or security systems. The main purpose of this study is to build a constant monitoring system with the help of a deep learning neural network and artificial intelligence by introducing a new fuzzification technique called Fuzzy Approximation Method (FAM). Even though there are many difficulties in image processing, the challenging task is to fix the variations of backgrounds during monitoring. Though different contributions on this issue have been made, the surveillance system still faces a deficit of efficiency. This study helps to give more accurate clarity of the image by processing or converting the data and values of the plots in the form of an image. The processed image is scanned in various stages of hidden layers and brings it to a form of plotting points, and the graph is generated by using MATLAB tool through artificial intelligence. Step-by-step algorithm is followed throughout the entire process. The processed values are again stored in a variable as a resultant value by using a neural ...