Face recognition using enhancement discrete wavelet transform based on MATLAB

Abdulrahman, Asma Abdulelah; Tahir, Fouad Shaker

doi:10.11591/ijeecs.v23.i2.pp1128-1136

Cited by 15 publications

(9 citation statements)

References 13 publications

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“…Genetic diseases like diabetes, lung diseases, bald head, and cancer may come for the person having similar facial features or structure of the body. Genetic rare diseases may be predicted for the person having same facial features within the family [4,5]. The study found that 8% of people had a hereditary condition, and the majority of them have comparable face traits.…”

Section: Introductionmentioning

confidence: 96%

Analysis of Genetic Face Images with Respect to Reflexology for Prediction of Diseases

Sivapatham¹,

Umamageswari²,

Annappan³

et al. 2023

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A genetic disease or disorders is a hereditary issue caused by one or more abnormalities formed in the genome. Genetic disorders can be monogenic, multifactorial, or chromosomal. Like genetic disorders, facial features are also passed down genetically. This paper proposes to identify genetic disorders from facial features. However, it does not explain which facial features led to its prediction. In order to overcome the issues, face reflexology regions are analysed to predict the genetic diseases. Face reflexology regions are related to the internal organs and structure of the body. Genetic faces are analyzed with respect to face reflexology regions for the prediction of genetic diseases. Feature vectors are generated for the reflexology regions using Local binary pattern (LBP) with the combination of high frequency and low frequency textures. The Euclidean distance weight function is used for prediction of diseases using the feature vectors. The proposed method is not only using single face reflexology regions, but combined reflexology regions of n persons are used for finding multiple possibility of diseases. Based on the statistical measure analysis, the proposed algorithm works well in extracting the features for identifying the diseases linked to genetic disorders, potentially speeding up diagnosis of diseases.

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Section: Introductionmentioning

confidence: 96%

Analysis of Genetic Face Images with Respect to Reflexology for Prediction of Diseases

Sivapatham¹,

Umamageswari²,

Annappan³

et al. 2023

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“…This paper was organized first, initializing the new discrete wavelet transformations derived from orthogonal aqueous polynomials in previous works that proved their worth in image processing and proving their mathematical aspects discrete laguerre wavelet transform (DLWT) [30]- [36]. Secondly, training the neural network AlexNet.…”

Section: Introductionmentioning

confidence: 99%

Distinguishing license plate numbers using discrete wavelet transform technology based deep learning

Abdulrahman¹,

Tahir²

2023

IJEECS

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Cars that violate the red light, and to increase the huge number of cars in violation, it is necessary to discover a system for identifying car plate numbers with the intervention of a computer, computer vision and neural networks segment and detail the number plates by designing regular algorithms to identify the number of license plates in violation. In this work, interest is in identifying the Iraqi car plate in order to know the place where the vehicle papers and the letters on which the vehicle depends and to know the location of the car were completed. The technique that was carried out in this work is to build new wavelets from polynomials by mathematical methods and discover a new algorithm using the MATLAB program to identify each number in the vehicle plate with a specific color by training a convolutional neural network (CNN) after analyzing the image using the new wavelets to identify the contents of the plate and good results have been reached. The accuracy level was reached with good values of up to 95%.

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“…Reserch from [20], [21] it produces two matrices after factoring low and upper matrix (LU) to be the principal diameter of 1. Solving this problem, the benefits of which are summarized in authentication data and copyright protection, so that the process is in two stages, is to hide the watermark information and restore it [22]- [24].…”

Section: Introductionmentioning

confidence: 99%

The effectiveness of discrete hermite wavelet filters technique in digital image watermarking

Abduldaim¹,

Abdulrahman²,

Tahir³

2022

IJEECS

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<span>In this work, new discrete wavelets were derived Hermite polynomials for obtained discrete hermite wavelet transformation (DHWT), and their efficiency for use in image processing is demonstrated by proving the realization of important theorems. Moreover, the role of the new and proposed waveforms in their effective effect in placing the watermark with the color image is clarified, and a program was created using MATLAB software by creating a subprogram for constructing the new wavelet and proving its efficiency with an analytic image. The process is repeated using DHWT to analyze the image. The color image has been subjected to various attacks after which the watermark is retrieved from the image after comparing it with the proposed algorithm and it has proven its power faster and better than the previously suggested methods. The final conclusion shows that using new wavelets DHWT better peak signal of noise ratio (PSNR)s can be obtained and that the proposed algorithm fills in better the lack of awareness of the watermark and its strength under different attacks.</span>

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Face recognition using enhancement discrete wavelet transform based on MATLAB

Cited by 15 publications

References 13 publications

Analysis of Genetic Face Images with Respect to Reflexology for Prediction of Diseases

Analysis of Genetic Face Images with Respect to Reflexology for Prediction of Diseases

Distinguishing license plate numbers using discrete wavelet transform technology based deep learning

The effectiveness of discrete hermite wavelet filters technique in digital image watermarking

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