This paper is published in Volume-3, Issue-5, 2017
Area
Image Processing
Author
Shubham Srivastav, Shyam Shankar Dwivedi
Org/Univ
Rameshwaram Institute of Education & Training, Lucknow, Uttar Pradesh, India
Keywords
Face Recognition, Face Detection, Euclidean Distance, Recognition Rate, Viola Jones.
Citations
IEEE
Shubham Srivastav, Shyam Shankar Dwivedi. A Hybrid Approach to Detect and Recognise Faces in Complex Background, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Shubham Srivastav, Shyam Shankar Dwivedi (2017). A Hybrid Approach to Detect and Recognise Faces in Complex Background. International Journal of Advance Research, Ideas and Innovations in Technology, 3(5) www.IJARIIT.com.
MLA
Shubham Srivastav, Shyam Shankar Dwivedi. "A Hybrid Approach to Detect and Recognise Faces in Complex Background." International Journal of Advance Research, Ideas and Innovations in Technology 3.5 (2017). www.IJARIIT.com.
Shubham Srivastav, Shyam Shankar Dwivedi. A Hybrid Approach to Detect and Recognise Faces in Complex Background, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Shubham Srivastav, Shyam Shankar Dwivedi (2017). A Hybrid Approach to Detect and Recognise Faces in Complex Background. International Journal of Advance Research, Ideas and Innovations in Technology, 3(5) www.IJARIIT.com.
MLA
Shubham Srivastav, Shyam Shankar Dwivedi. "A Hybrid Approach to Detect and Recognise Faces in Complex Background." International Journal of Advance Research, Ideas and Innovations in Technology 3.5 (2017). www.IJARIIT.com.
Abstract
Face recognition from image or video is a popular topic in biometrics research. In this research work a new hybrid approach to detect and recognize faces is proposed and implemented. The proposed algorithm uses Viola Jones method to detect face area from a complex background and then uses the same image to create a database of images. In the recognition part, it again detects the face area and computes the Euclidean Distance of the current face with that of the face images in the training database. The minimum Euclidean distance parameter is used to recognize the correct face, if it is available in the database. The algorithm shows good results in terms of recognition rate as compared to some previous research work in similar field.
