Face Detection using Support Vector Mechine with PCA

5 Pages Posted: 9 Jan 2020

See all articles by Pranati Rakshit

Pranati Rakshit

JIS College of Engineering - Department of Computer Science and Engineering

Rajit Basu

JIS College of Engineering - Department of Computer Science and Engineering

Sayan Paul

JIS College of Engineering - Department of Computer Science and Engineering

Sonali Bhattacharyya

JIS College of Engineering - Department of Computer Science and Engineering

Jhumpa Mistri

JIS College of Engineering - Department of Computer Science and Engineering

Ira Nath

JIS College of Engineering - Department of Computer Science and Engineering

Date Written: January 8, 2020

Abstract

Face recognition is a popular subject in biometrics research which has distinct advantages because of its non-contact process. This technology has gained popularity because of its large application value and market value, like video surveillance system for real time tracking of suspicious object. In this paper we focus on the image face which has to be correctly recognized using support vector Machine (SVM) techniques with Principle Components Analysis (PCA) which extract the features and reduce dimensionality. Also we have used KNN classifier. The SVM with PCA produces more accurate result compare to other methods. This paper achieved 92% successful recognition rate for detecting different face databases.

Keywords: Face detection, Face Recognition, PCA, SVM, KNN

Suggested Citation

Rakshit, Pranati and Basu, Rajit and Paul, Sayan and Bhattacharyya, Sonali and Mistri, Jhumpa and Nath, Ira, Face Detection using Support Vector Mechine with PCA (January 8, 2020). 2nd International Conference on Non-Conventional Energy: Nanotechnology & Nanomaterials for Energy & Environment (ICNNEE) 2019, Available at SSRN: https://ssrn.com/abstract=3515989 or http://dx.doi.org/10.2139/ssrn.3515989

Pranati Rakshit (Contact Author)

JIS College of Engineering - Department of Computer Science and Engineering ( email )

India

Rajit Basu

JIS College of Engineering - Department of Computer Science and Engineering ( email )

India

Sayan Paul

JIS College of Engineering - Department of Computer Science and Engineering ( email )

India

Sonali Bhattacharyya

JIS College of Engineering - Department of Computer Science and Engineering ( email )

India

Jhumpa Mistri

JIS College of Engineering - Department of Computer Science and Engineering ( email )

India

Ira Nath

JIS College of Engineering - Department of Computer Science and Engineering ( email )

India

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