Preferred Language
Articles
/
jih-2527
Performance Enhancement of Face Recognition under High-Density Noise Using PCA and De-Noising Technique
...Show More Authors

       There are many techniques for face recognition which compare the desired face image with a set of faces images stored in a database. Most of these techniques fail if faces images are exposed to high-density noise. Therefore, it is necessary to find a robust method to recognize the corrupted face image with a high density noise. In this work, face recognition algorithm was suggested by using the combination of de-noising filter and PCA. Many studies have shown that PCA has ability to solve the problem of noisy images and dimensionality reduction. However, in cases where faces images are exposed to high noise, the work of PCA in removing noise is useless, therefore adding a strong filter will help to improve the performance of recognizing faces in the case of existing high-density noise in faces images. In this paper, Median filter, Hybrid Median Filter, Adaptive Median filter, and Adaptive Weighted Mean Filter were used to remove the noise from the faces images, and they were compared in order to use the best of these filters as a pre-processing step before the face recognition process. Experimental results showed that the Adaptive Weighted Mean Filter gave better results compared with the other filters. Thus, the performance of face recognition process was improved under high-density noise using the Adaptive Weighted Mean Filter and Principal Component Analysis. For the corrupted images by 90 % noise density, Recognition rate by using Median Filter reached 0% and 33% by using Hybrid Median Filter. While Recognition rate by using the Adaptive Median Filter and Adaptive Weighted Mean Filter reached 100%.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Advanced Computer Science And Applications
Face Detection and Recognition Using Viola-Jones with PCA-LDA and Square Euclidean Distance
...Show More Authors

View Publication
Crossref (25)
Crossref
Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Finger Vein Recognition Based on PCA and Fusion Convolutional Neural Network
...Show More Authors

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

... Show More
Publication Date
Wed Oct 25 2023
Journal Name
Plos One
Performance enhancement of high order Hahn polynomials using multithreading
...Show More Authors

Orthogonal polynomials and their moments have significant role in image processing and computer vision field. One of the polynomials is discrete Hahn polynomials (DHaPs), which are used for compression, and feature extraction. However, when the moment order becomes high, they suffer from numerical instability. This paper proposes a fast approach for computing the high orders DHaPs. This work takes advantage of the multithread for the calculation of Hahn polynomials coefficients. To take advantage of the available processing capabilities, independent calculations are divided among threads. The research provides a distribution method to achieve a more balanced processing burden among the threads. The proposed methods are tested for va

... Show More
View Publication
Scopus (4)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using Wavelet Network
...Show More Authors

 

            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

View Publication Preview PDF
Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
A comparison between PCA and some enhancement filters for denoising astronomical images
...Show More Authors

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Jan 01 2013
Journal Name
Iraqi Journal Of Physics
A comparison between PCA and some enhancement filters for denoising astronomical images
...Show More Authors

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

... Show More
Publication Date
Thu Feb 01 2024
Journal Name
Ain Shams Engineering Journal
Performance enhancement of high degree Charlier polynomials using multithreaded algorithm
...Show More Authors

View Publication
Scopus Clarivate Crossref
Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
...Show More Authors
Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
View Publication
Scopus (6)
Crossref (2)
Scopus Crossref
Publication Date
Fri May 04 2018
Journal Name
Wireless Personal Communications
IFRS: An Indexed Face Recognition System Based on Face Recognition and RFID Technologies
...Show More Authors

View Publication
Scopus (10)
Crossref (8)
Scopus Clarivate Crossref
Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
...Show More Authors

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (2)
Scopus Clarivate Crossref