Peculiarities of face detection and recognition

Mamatov, N.; Bakhtiyor, Abdukadirov; Kakharov, Shukrullo; Bakhodirjon, Orifjonov; Gulbahor, Abdukadirova

doi:10.1109/icisct52966.2021.9670086

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…Let there be a set of F objects presented in the form of images of faces. The initial data about each object F is given in the form of a matrix X of size m × n (where m and n are the number of rows (images) and the number of columns (features), respectively) [8]:…”

Section: Basic Concepts and Notationmentioning

confidence: 99%

“…The algorithms in (8) solve the recognition problem with varying accuracy. Considering (4), instead of recognition algorithms (8) consider the set of corresponding recognition operators, which we denote by B:…”

Section: Statements Of the Problemmentioning

confidence: 99%

“…A holistic approach to face recognition is mainly represented by Eigenface and Fisherface methods [5], independent component analysis (ICA) [6], moment invariants [7], discrete cosine transform (DCT) [8] etc. The component-based approach is implemented in the following widely used methods: support vector machine (SVM) [9], linear discriminant analysis (LDA) [10], statistical methods [11,12] etc.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Ensemble Approach To Face Recognition In Access Control Systems

Opanasenko,

Fazilov,

Mirzaev

et al. 2024

JMM

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The article proposes a method for recognizing faces in mobile devices, based on an ensemble approach to solving the problem of pattern recognition, which ensures high accuracy of results. According to this approach, the basic algorithm is decomposed into two operators: a recognition operator and a decision rule. The recognition operator calculates estimates of the proximity of the tested object to the given classes. The decision rule, based on these estimates, determines whether the tested object belongs to one of the given classes. The ensemble of recognizing operators is formed in the form of a linear polynomial. The values of the polynomial parameters are calculated based on the solution of the multiparameter optimization problem. Experimental studies were carried out using open databases of facial images. When conducting experiments, it was assumed that two options for using basic algorithms would be implemented: separate and ensemble. The accuracy of recognizing objects in the control sample using an ensemble of recognition operators turned out to be higher compared to the accuracy of the best basic recognition algorithm. The proposed face recognition method can be used in mobile devices, in particular, to verify users when remotely accessing information resources that limited access status.

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Section: Basic Concepts and Notationmentioning

confidence: 99%

Section: Statements Of the Problemmentioning

confidence: 99%