A new hybrid face recognition algorithm based on discrete wavelet transform and direct LDA

2016 ◽  
Author(s):  
Seyyed Amir Ziafati Bagherzadeh ◽  
Alireza Noei Sarcheshmeh ◽  
Seyyed Hassan Ziafati Bagherzadeh ◽  
Mohammad Mahdi Khalilzadeh
Keyword(s):  
Face Recognition ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Recognition Algorithm ◽  
Discrete Wavelet

TWO-DIMENSIONAL STATIONARY DYADIC WAVELET TRANSFORM, DECIMATED DYADIC DISCRETE WAVELET TRANSFORM AND THE FACE RECOGNITION APPLICATION

2011 ◽  
Vol 09 (03) ◽  
pp. 397-416 ◽  
Author(s):  
YANKUI SUN ◽  
YONG CHEN ◽  
HAO FENG
Keyword(s):  
Face Recognition ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Recognition Algorithm ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Wavelet Filters ◽  
Dyadic Wavelet ◽  
Dyadic Wavelet Transform ◽  
Approximation Coefficients

Currently, two-dimensional dyadic wavelet transform (2D-DWT) is habitually considered as the one presented by Mallat, which is defined by an approximation component, two detail components in horizontal and vertical directions. This paper is to introduce a new type of two-dimensional dyadic wavelet transform and its application so that dyadic wavelet can be studied and used widely furthermore. (1) Two-dimensional stationary dyadic wavelet transform (2D-SDWT) is proposed, it is defined by approximation coefficients, detail coefficients in horizontal, vertical and diagonal directions, which is essentially the extension of two-dimensional stationary wavelet transform for orthogonal/biorthogonal wavelet filters. (2) ε-decimated dyadic discrete wavelet transform (DDWT) is introduced and its relation with 2D-SDWT is given, where ε is a sequence of 0's and 1's. (3) Mallat decomposition algorithm based on dyadic wavelet is introduced as a special case of ε-decimated DDWT, and so a face recognition algorithm based on dyadic wavelet is proposed, and experimental results are given to show its effectiveness.

scholarly journals Technical Vision System for in-Room Access Control

2021 ◽  
Vol 4 (4) ◽  
Author(s):  
Artem Ihorovych Fironov ◽  
Vitaliy Viktorovych Levchenko
Keyword(s):  
Face Recognition ◽  
Wavelet Transform ◽  
Standard Deviation ◽  
Access Control ◽  
Discrete Wavelet Transform ◽  
Output Signal ◽  
Discrete Wavelet ◽  
Pass Filter ◽  
Technical Vision ◽  
Speed Up

Access systems with face recognition is widely used today. They are used in many enterprises and institutes where it is necessary to control the flow of passing people.  Facially recognizable technical vision systems are important because they can be used to store specific individuals faces and use them for access control. As a result of analysis of same modern systems the variant of system there are additional functions is offered. The system consists of ESP-EYE module, with build-in wi-fi and Bluetooth modules, chip sensor camera “ OV2640” and LED display, which dasplays a notification for a person about granting or denying access, notifications are in two collors: geen and red respectively.. Also it has an emergency power supply in case of unforeseen situations. Wi-fi is used as a means of transmiting data from camera to the server. This transmition method of data transmition has several advantages over Bluetooth. It allows to the system to transfer data at a much higher speed and over a grater distance, it is also more secure, provides access to the internet and allows to control the system  remotely. All the listed advantages of this method of transmition give us a great variability in the operation and placement of the system. To recognize people system use a comparison method. It compares the person’s face with a database and, after processing it produces the result. To optimize and speed up this process, the system uses a method of image compression based on discrete wavelet transform. This method is the transmission of a signal through several filtres, usualy two. First, the signal is passed through a low-pass filter whis a pulse response g, resulting in an output signal in the form of a convolutional sum. At the same time the signal is decomposed by a high pass filter. The LPF gives an approximate shape of the output signal, and the HPF – the signal of difference or additional detail. Discrete wavelet transform in an oriented basis makes it possible to construct transformation matrices with a given number of filters ”m”, where “m” is in the general case a prime positive number. The simplest way to compare the two images is by substracting the brightness values of the two matrices and estimating the resulting matrix of differences using standard deviation. The use of standard deviation in combination with fiberboard in OB allows to speed up the process of face recognition in the system by discarding unncessary details, the absence of which minimaly harms the accuracy of the results. The advantages of this system are that it is less expensive, in compareson with existing analogs, less energy-consuming, easy to assemble and install, uses a relatively simple and at the same time quite accurate method of identidying a persons identity.

Near infrared face recognition by combining Zernike moments and undecimated discrete wavelet transform

2014 ◽  
Vol 31 ◽  
pp. 13-27 ◽  
Author(s):  
Sajad Farokhi ◽  
Siti Mariyam Shamsuddin ◽  
U.U. Sheikh ◽  
Jan Flusser ◽  
Mohammad Khansari ◽  
...  
Keyword(s):  
Face Recognition ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Near Infrared ◽  
Zernike Moments ◽  
Discrete Wavelet
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