RFID ACCESS AUTHORIZATION BY FACE RECOGNITION 報告學生：翁偉傑 1 Proceedings of the Eighth International Conference on Machine Learning and Cybernetics, Baoding, July 2009

OUTLINE Introduction Security System for RFID Access Control Face Feature Extraction with SIFT L-GEM Trained RBFNN based Face Recognizer Experimental Results Conclusions 2

INTRODUCTION Radio Frequency Identification (RFID) 的主要缺點， 任何人都可以得到該卡存取。 本研究提出了一種基於神經網絡的人臉識別系統， 本研究提出了一個 Localized Generalization Error Model (L-GEM) 的徑向 Radial Basis Function Neural Network (RBFNN) 人臉辨識系統，以提高 安全性的 RFID 卡的系統。 3

SECURITY SYSTEM FOR RFID ACCESS CONTROL (1/2) 4 The Processes of Security System Training

SECURITY SYSTEM FOR RFID ACCESS CONTROL (2/2) 5 The Processes of the Security System

FACE FEATURE EXTRACTION WITH SIFT (1/3) 6 範例： SIFT 它的穩定性和精度高優於其他描述。

FACE FEATURE EXTRACTION WITH SIFT (2/3) 7 Local Feature Descriptors of Two Images of the Same Person

FACE FEATURE EXTRACTION WITH SIFT (3/3) 8 The Local Feature Descriptors of Two Images of Two Different People

L-GEM TRAINED RBFNN BASED FACE RECOGNIZER (1/3) 9 The RBFNN is trained as follows: 1. Store the RFID card owner information in the database and take 10 images of the owner 2. L-GEM trained RBFNN to recognize face of person. 3. The trained RBFNN is then stored in the database and associated with the card owner.

L-GEM TRAINED RBFNN BASED FACE RECOGNIZER (2/3) 10 is a general framework to estimate the localized generalization error of a classifier where N, Remp and SM denote the number of training samples, the training mean square error and the stochastic sensitivity measure of RBFNN, respectively.

L-GEM TRAINED RBFNN BASED FACE RECOGNIZER (3/3) 11 The procedures for the face recognition after reading the RFID card ID is as follows: 1. Fetch the card owner’s RBFNN from the database 2. Face Detection by Adaboost and output a small image with face only 3. Extract local feature descriptor from the detected face image 4. Classify the face by the RBFNN trained by the L-GEM 5. If the face owner does not match the RFID card owner, alert security, otherwise end

EXPERIMENTAL RESULTS (1/4) In this experiment, we assume that there are 3 users of the security system. Each of them holds an RFID card. The system is built to verify whether the card holder is the card owner. We name these 3 people as Person A, Person B and Person C for convenience. 以 10 張為訓練圖像。 實驗 90 次，分為 30 次 ( 個人 ) 和 60 次 ( 混合 ) 。 12

EXPERIMENTAL RESULTS (2/4) 13 Training Images of Person A

EXPERIMENTAL RESULTS (3/4) 14 Moving in the entranceA face is detected Tracing the detected face The Face leaving

EXPERIMENTAL RESULTS (4/4) 15 Testing Results of the Security System

CONCLUSIONS This research proposed a security system combining RFID card access control with face recognition by RBFNN trained by the L-GEM. enhance security of RFID card based access control systems Can only recognize one person per access. 16