OPEN SOURCE CODE-FACE PARTS DETECTION USING MATLAB
DESIGN DETAILS
Face recognition is one of the most popular applications for automatically identifying or verifying a person, being an important area of research in computer vision. It is a form of biometric identification based on physiological characteristics of the face and it is totally non-intrusive. One of the main critical point in the face recognition applications is the execution time required by the image processing algorithms. The size of images necessary for recognizing and the demand for real-time operation increases the exigencies in the processing time and, therefore, the need to design efficient and high-performance image processing systems. Nose, Eye and mouth state analysis is an important step in fatigue detection. This Matlab design is based on detection of nose, eyes and mouth in face recognition using Matlab, first the face area is detected from the input video from the database then applying inbuilt commands to find the nose, eyes, and mouth.
REQUEST THE SOURCE CODE FROM THE BELOW URL WITH COLLEGE/UNIVERSITY E-MAIL ID,
https://drive.google.com/file/d/1-zcf...
REFERENCES
Reference Paper-1: Eye and mouth state detection algorithm based on contour feature extraction
Author’s Name: Yingyu Ji, Shigang Wang, Yang Lu, Jian Wei, and Yan Zhao
Source: Journal of Electronic Imaging
Year: 2018
You may contact +91 7904568456 by WhatsApp Chat, for paid services.
We are available on Telegram and Signal.
Visit Website: http://www.verilogcourseteam.com/
Visit Our Social Media
Like our Facebook Page: / verilogcourseteam
Subscribe: / verilogcourseteamelectricalprojects
Subscribe: / verilogcourseteammatlabproject
Subscribe: / verilogcourseteam
On this page of the site you can watch the video online OPEN SOURCE CODE-FACE PARTS DETECTION USING MATLAB with a duration of hours minute second in good quality, which was uploaded by the user VERILOG COURSE TEAM-MATLAB PROJECT 09 January 2022, share the link with friends and acquaintances, this video has already been watched 244 times on youtube and it was liked by 3 viewers. Enjoy your viewing!
