2D Face Recognition Using Interval Type-2 Fuzzy Logic

This book is organized as follows: Chapter 2: covers the background and literature survey on face Recognition issues, the taxonomy of face Recognition process, and face recognition algorithms. Chapter 3: describes, in detail, the proposed face Recognition method that utilizes Interval Type-2 Fuzzy Logic to the treatment of uncertainty in 2D face recognition systems. Chapter 4: reports selected results from the experimental evaluation including several experimental results performed to ascertain and assess the accuracy and robustness of the proposed approach. Chapter 5: conclusions are presented in this chapter indicating the improved performance to the proposed approach 2D face recognition system based on fisher discriminant criterion and fuzzy set theory. The system calculates membership degree matrix through a generalized version of fuzzy KNN algorithm called interval type-2 fuzzy KNN that includes refined information about class membership of the patterns.

Autorentext

received the B.Sc. degree in Mathematics/ Computer Branch, University of Mosul, Iraq in 1990, and 2013, M.Sc. in Information Technology, Alexandria University, On 2016, he received his doctoral degree in Information Technology,Alexandria University. His research and professional interests include image processing and security technologies.