• APURWA V. ATRE
• DR. MRS. R. A. KHAN

Face recognition has gained a significant position among most commonly used applications of image processing. With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. Partial face images are produced in an unconstrained environment. A face may be occluded by sunglasses, a hat and a scarf, captured in various poses, positioned partially out of cameras field of view. Human face plays an important role in our social interaction, conveying people’s identity but it is a dynamic object and has a high degree of variability in its appearances. The problem of recognizing an arbitrary patch of a face image remains largely unsolved. This study proposes a new partial face recognition approach, called Dynamic Feature Matching, which combines Fully Convolutional Networks, Principle Component Analysis and Sparse Representation Classification to address partial face recognition problem regardless of various face sizes. DFM does not require prior position information of partial faces against a holistic face.

Dynamic feature matching, Partial face recognition, Gabor filter, Principle component Analysis, Fully convolutional network.

"A Survey on Face Recognition System by using a Principle Component Analysis and Fully Convolutional Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 6, page no.345-347, June-2020, Available :http://www.jetir.org/papers/JETIR2006389.pdf

"A Survey on Face Recognition System by using a Principle Component Analysis and Fully Convolutional Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp345-347, June-2020, Available at : http://www.jetir.org/papers/JETIR2006389.pdf