INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Identifying Human Face under video surveillance using Machine Learning Technique
Authors Name:
Ashok R. Avachar
, Dr Shubhangi D. Sapkal , N Dr. Ratnadeep R. Deshmukh
Unique Id:
IJSDR1910001
Published In:
Volume 4 Issue 10, October-2019
Abstract:
Automatic Physiognomy recognition systems are now popularly used in various applications ranging from mobile payment verification to inbuild security access. The use of Physiognomy recognition has increased awareness about facial simulation attacks viz is also called as a biometric sensor presentation attack) that can use a picture or motion file of the Physiognomy of an known person with access to facilities or services. While the amount of Physiognomy identification methodologies that have been proposed do have the ability to place general implications however they are not adequately addressed that is why we offer a powerful and robust Physiognomy detection algorithm using image distortion analysis (IDA). Four different properties (Spectrum deflection, interval, color, and variety with colors) these can be separated to create an IDA class feature set vector, which consists of several SVM classifiers that have been trained for disguised Physiognomy forgery. (Eg printed photos and replayed videos) that are utilized to distinguish between true Physiognomy and pseudo-physiognomy. The method that is addressed here covers detecting multiple Physiognomy in a video using voting patterns.
Keywords:
Component, formatting, style, styling, insert
Cite Article:
"Identifying Human Face under video surveillance using Machine Learning Technique", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 10, page no.1 - 8, October-2019, Available :http://www.ijsdr.org/papers/IJSDR1910001.pdf
Downloads:
000336256
Publication Details:
Published Paper ID: IJSDR1910001
Registration ID:191013
Published In: Volume 4 Issue 10, October-2019
DOI (Digital Object Identifier):
Page No: 1 - 8
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
Facebook Twitter Instagram LinkedIn