scholarly journals A Novel Principal Component Analysis Color Identification Algorithm for Moving Plate Recognition system

IERI Procedia ◽  
2012 ◽  
Vol 2 ◽  
pp. 102-107 ◽  
Author(s):  
Yu Chen ◽  
Jun Cao ◽  
Aifei Wang
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Recognition System ◽  
Identification Algorithm ◽  
Moving Plate ◽  
Color Identification

HUMAN FACE DETECTION USING SILHOUETTES

1995 ◽  
Vol 09 (06) ◽  
pp. 845-867 ◽  
Author(s):  
ASHOK SAMAL ◽  
PRASANA A. IYENGAR
Keyword(s):  
Principal Component Analysis ◽  
Face Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Recognition System ◽  
Human Face ◽  
Secure Systems ◽  
Human Face Detection ◽  
Intensity Images ◽  
Human Faces

Face detection is integral to any automatic face recognition system. The goal of this research is to develop a system that performs the task of human face detection automatically in a scene. A system to correctly locate and identify human faces will find several applications, some examples are criminal identification and authentication in secure systems. This work presents a new approach based on principal component analysis. Face silhouettes instead of intensity images are used for this research. It results in reduction in both space and processing time. A set of basis face silhouettes are obtained using principal component analysis. These are then used with a Hough-like technique to detect faces. The results show that the approach is robust, accurate and reasonably fast.

scholarly journals Principal component analysis for human gait recognition system

2019 ◽  
Vol 8 (2) ◽  
pp. 569-576
Author(s):  
Othman O. Khalifa ◽  
Bilal Jawed ◽  
Sharif Shah Newaj Bhuiyn
Keyword(s):  
Principal Component Analysis ◽  
Minimum Distance ◽  
Gait Recognition ◽  
Principal Component ◽  
Initial Step ◽  
Component Analysis ◽  
Recognition System ◽  
Human Gait ◽  
The One ◽  
Main Components

This paper represents a method for Human Recognition system using Principal Component Analysis. Human Gait recognition works on the gait of walking subjects to identify people without them knowing or without their permission. The initial step in this kind of system is to generate silhouette frames of walking human. A number of features couldb be exytacted from these frames such as centriod ratio, heifht, width and orientation. The Principal Component Analysis (PCA) is used for the extracted features to condense the information and produces the main components that can represent the gait sequences for each waiking human. In the testing phase, the generated gait sequences are recognized by using a minimum distance classifier based on eluclidean distance matched with the one that already exist in the database used to identify walking subject.

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