Applications of PCA and SVM-PSO Based Real-Time Face Recognition System
نویسندگان
چکیده
منابع مشابه
A Real-time Intrusion Detection System Based on PSO-SVM
The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with irrelevant and redundant features. How to choose the effective and key features to IDS is very important topic in information security. Support vector machine (SVM) has been employed to provide potential solutions for the IDS p...
متن کاملOptimized Method for Real-Time Face Recognition System Based on PCA and Multiclass Support Vector Machine
Automatic face recognition system is one of the core technologies in computer vision, machine learning, and biometrics. The present study presents a novel and improved way for face recognition. In the suggested approach, first, the place of face is extracted from the original image and then is sent to feature extraction stage, which is based on Principal Component Analysis (PCA) technique. In t...
متن کاملEvaluation of face recognition techniques using PCA, wavelets and SVM
In this study, we present an evaluation of using various methods for face recognition. As feature extracting techniques we benefit from wavelet decomposition and Eigenfaces method which is based on Principal Component Analysis (PCA). After generating feature vectors, distance classifier and Support Vector Machines (SVMs) are used for classification step. We examined the classification accuracy ...
متن کاملFace recognition approach using Gabor Wavelets, PCA and SVM
Face recognition is an important research field of pattern recognition. Up to now, it caused researchers great concern from these fields, such as pattern recognition and computer vision. In general, we can make sure that the performance of face recognition system is determined by how to extract feature vector exactly and to classify them into a class correctly. Therefore, it is necessary for us...
متن کاملFace Recognition Technique Using PCA, Wavelet and SVM
Biometric-based technologies include the identification based on physiological characteristics such as face, fingerprints, hand geometry, hand veins, palm, iris, retina, ear, voice and behavioral traits such as gait, signature and keystroke dynamics [1]. These biometric technologies require some voluntary action by the user. However, face recognition can be done passively without any explicit a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2014
ISSN: 1024-123X,1563-5147
DOI: 10.1155/2014/530251