Face Recognition System in Cell Phones Based on Text Message Service

Author(s):  
Suman Deb ◽  
Sourav Biswas ◽  
Chinmoy Debnath ◽  
Suddhasatta Dhar ◽  
Priyanka Deb
Author(s):  
Rutuja Parge ◽  
Nilam Patil ◽  
Pooja Yelve ◽  
Prof. Vidhya Gavali

Lost Humans in our country and in different nations that they are known by everybody to be a significant social issue. These days distinguishing proof of a specific individual in the packed territory is a perplexing assignment. The human face assumes a significant part in our social communication, passing on individuals' personality. Face acknowledgment is an errand that people perform regularly and easily in their everyday lives. Face acknowledgment, as one of the essential biometric advances, turned out to be increasingly more significant inferable from fast advances in advances like computerized cameras, the Internet and cell phones, and expanded requests on security. For this, an answer is furnished on this with the assistance of a profound learning idea. Convolutional Neural Network (CNN) is utilized for the recognizable proof of an individual. The missing individual is distinguished utilizing different facial highlights. Face Detection assumes a significant part in this task. This framework tends to the structure of face acknowledgment framework by utilizing CNN technique. The CNN has been widely utilized for face acknowledgment calculations. It decreases the dimensionality of the picture, yet additionally holds a portion of the varieties in dataset of images.


2020 ◽  
Vol 1601 ◽  
pp. 052011
Author(s):  
Yong Li ◽  
Zhe Wang ◽  
Yang Li ◽  
Xu Zhao ◽  
Hanwen Huang

Author(s):  
CHING-WEN CHEN ◽  
CHUNG-LIN HUANG

This paper presents a face recognition system which can identify the unknown identity effectively using the front-view facial features. In front-view facial feature extractions, we can capture the contours of eyes and mouth by the deformable template model because of their analytically describable shapes. However, the shapes of eyebrows, nostrils and face are difficult to model using a deformable template. We extract them by using the active contour model (snake). After the contours of all facial features have been captured, we calculate effective feature values from these extracted contours and construct databases for unknown identities classification. In the database generation phase, 12 models are photographed, and feature vectors are calculated for each portrait. In the identification phase if any one of these 12 persons has his picture taken again, the system can recognize his identity.


Sensors ◽  
2014 ◽  
Vol 14 (11) ◽  
pp. 21726-21749 ◽  
Author(s):  
Won Lee ◽  
Yeong Kim ◽  
Hyung Hong ◽  
Kang Park

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