Propose an Efficient Face Recognition Model in WSN Based on Zak Transform

Abstract

The need for a flexible and cost effective biometric security system is the inspired of this paper. Face recognition is a good contactless biometric and it is suitable and applicable for Wireless Sensor Network (WSN). Image processing and image communication is a challenges task in WSN due to the heavy processing and communication that reduce the life time of the network. This paper proposed a face recognition algorithm on WSN depending on the principles of the unique algorithm that hold the capacity of the network to the sink node and compress the communication data to 89.5%. An efficient hybrid method is introduced based upon the advantage of Zak transform to offprint the farthest different features of the face and Eigen face method to assort acceding to the minimum value of the distance with feature vectors on a flat architecture to the WSN with gossiping routing protocol. An Excellent recognition rate is achieved reaching to 100% with a minimum computation time.