37

Бугунги кунда хавфсизлик тизимларида биометрикадан фойдаланиш оммалашиб бормоқда. Биометрикага асосланган тизимлар ҳар бир инсонни анатомик ўзига хослигига асосланади. Анатомик белгиларга юз, кўз қорачиғи, бармоқ излари, кафт каби биометрик белгилар киради. Юзни аниқлаш тизим самарадорлиги юздаги белгиларни ажратиб олиш самарадорлигига бевосита боғлиқ. Юз тасвири асосида шахсни таниб олиш одатда локал ва глобал белгилар асосида амалга оширилади. Локал белгиларни шакллантиришда юз тасвири алоҳида қисмларга ажратилади ва шакллантирилган локал белгилар асосида таниб олиш амалга оширади. Глобал белгиларни ажратиш эса бутун юз тасвирида белгиларни шакллантиришдан иборат бўлиб, улардан информативларини ажратиш орқали таниб олиш харажатларини камайтириш мумкин.Мазкур мақола юз тасвири информатив белгилар фазосини шакллантириш алгоритмларини таҳлилига бағишланган бўлиб, унда информатив белгиларни аниқлаш процедураси баён этилган бўлиб, юз тасвири информатив белгиларини ажратиш усул ва алгоритми таклиф этилган

  • Ўқишлар сони 37
  • Нашр санаси 01-04-2024
  • Мақола тилиO'zbek
  • Саҳифалар сони29-42
Ўзбек

Бугунги кунда хавфсизлик тизимларида биометрикадан фойдаланиш оммалашиб бормоқда. Биометрикага асосланган тизимлар ҳар бир инсонни анатомик ўзига хослигига асосланади. Анатомик белгиларга юз, кўз қорачиғи, бармоқ излари, кафт каби биометрик белгилар киради. Юзни аниқлаш тизим самарадорлиги юздаги белгиларни ажратиб олиш самарадорлигига бевосита боғлиқ. Юз тасвири асосида шахсни таниб олиш одатда локал ва глобал белгилар асосида амалга оширилади. Локал белгиларни шакллантиришда юз тасвири алоҳида қисмларга ажратилади ва шакллантирилган локал белгилар асосида таниб олиш амалга оширади. Глобал белгиларни ажратиш эса бутун юз тасвирида белгиларни шакллантиришдан иборат бўлиб, улардан информативларини ажратиш орқали таниб олиш харажатларини камайтириш мумкин.Мазкур мақола юз тасвири информатив белгилар фазосини шакллантириш алгоритмларини таҳлилига бағишланган бўлиб, унда информатив белгиларни аниқлаш процедураси баён этилган бўлиб, юз тасвири информатив белгиларини ажратиш усул ва алгоритми таклиф этилган

English

Today, the use of biometrics in security systems is becoming popular. Biometrics-based systems are based on the anatomical uniqueness of each person. Anatomical features include biometric features such as face, pupil, fingerprint, and palm. The performance of the face recognition system is directly related to the performance of face feature extraction. Facial recognition is usually based on local and global features. In the formation of local features, the face image is divided into separate parts, and recognition is performed based on the formed local features. Global feature extraction is the formation of features in the entire face image, and the cost of recognition can be reduced by separating the informative ones from them.In this article, the algorithms for creating the informative feature space for faces are analyzed, the process for locating informative features is explained, and a technique and algorithm for differentiating between face image informative features are suggested

Ҳавола номи
1 1.Kosolapov, A.M. Methods of analysis and synthesis of invariant transformation devices: Textbook. / A. M. Kosolapov // Samara. SamGTU. -2000. -86c.2.Kosolapov, A.M. Automation of simulation modeling of the measuring transducer / A. M. Kosolapov, S. V. Dumin // Metrology -2008. -No. 7 -P. 10-18.3.Kosolapov, A.M. Control systems. Methods of analysis and synthesis of linear systems: Textbook. / A. M. Kosolapov // Samara. SamGTU. -2003. -106c.4.Mamatov, N. S., Niyozmatova, N. A., Jalelova, M. M., Samijonov, A. N., & Tojiboyeva, S. X. (2023). Methods for improving contrast of agricultural images. In E3S Web of Conferences (Vol. 401, p. 04020). EDP Sciences. https://doi.org/10.1051/e3sconf/202340104020 5.Mamatov, N. S., Pulatov, G. G., & Jalelova, M. M. (2023). Image contrast enhancement method and contrast evaluation criteria optimal pair. Digital Transformation and Artificial Intelligence, 1(2).6.Mamatov, N. S., Jalelova, M. M., Samijonov, A. N., & Samijonov, B. N. (2024, February). Algorithm for improving the quality of mixed noisy images. In Journal of Physics: Conference Series (Vol. 2697, No. 1, p. 012013). IOP Publishing. https://doi.org/ 10.1088/1742-6596/2697/1/012013 7.Mamatov, N., Jalelova, M., & Samijonov, B. (2024). Tasvir obyektlarini segmentatsiyalashning mintaqaga asoslangan usullari. Modern Science and Research, 3(1), 1-4. https://inlibrary.uz/index.php/science-research/article/view/28241 8.Mamatov, N., Jalelova, M., Samijonov, B., & Samijonov, A. (2024). Algorithms for contour detection in agricultural images. In E3S Web of Conferences (Vol. 486, p. 03017). EDP Sciences. https://doi.org/10.1051/e3sconf/202448603017 9.Mamatov, N., Jalelova, M., Samijonov, B., & Samijonov, A. (2024). Algorithm for extracting contours of agricultural crops images. In ITM Web of Conferences (Vol. 59, p. 03015). EDP Sciences. https://doi.org/10.1051/itmconf/20245903015 10.Mamatov, N., Sultanov, P., Jalelova, M., & Samijonov, A. (2023). 2D image processing algorithms for kidney transplantation. Scientific Collection «InterConf», (184), 468-474. 11.Solidjonovich, M. N., Qizi, J. M. M., Qizi, T. S. X., & O’G’Li, S. B. N. (2023). SUN’IY YO’LDOSHDAN OLINGAN TASVIRDAGI DALA MAYDONI CHEGARALARINI ANIQLASH USULLARI. Al-Farg’oniy avlodlari, 1(4), 177-181.12.Маматов, Н., Султанов, П., Жалелова, М., & Тожибоева, Ш. (2023). Критерии оценки качества медицинских изображений, полученных на мультиспиральном компьютерном томографе. Евразийский журнал математической теории и компьютерных наук, 3(9), 27-37.13.Маматов, Н., Султанов, П., Юлдашев, Ю., & Жалелова, М. (2023). Методы повышения контрастности изображений при мультиспиральной компьютерной томографии. Евразийский журнал академических исследований, 3(9), 125-132.14.Маматов, Н., & Джалелова, М. (2023). Tasvir shovqinlari tahlili. Информатика и инженерные технологии, 1(2), 113-115.15.Маматов, Н., & Джалелова, М. (2023). Tasvir kontrastini etalonsiz baholash. Информатика и инженерные технологии, 1(2), 115-117.16.Маматов, Н., Рахмонов, Э., Самижонов, А., Жалелова, М., & Самижонов, Б. (2023). ТАСВИРДАГИ МИКРОСКОПИК ОБЪЕКТЛАРНИ ТАНИБ ОЛИШ АЛГОРИТМЛАРИ. Евразийский журнал математической теории и компьютерных наук, 3(11), 7-13.17.Yang, M.H. Detecting faces in images: A survey / M. H. Yang, D. J. Kriegman, N. Ahuja // IEEE Trans. P.A.M.I. -2002. -T. 24 -No. 1 -C. 34-58.18.Sakovich, I.O. Overview of the main methods of contour analysis for the selection of contours of moving objects / I. O. Sakovich, Yu. S. Belov // Engineering Journal: Science and Innovations. -2014. -No. 12 -S. 1-8.19.Shavkat, F., Narzillo, M., & Nilufar, N. (2019). Developing methods and algorithms for forming of informative features’ space on the base K-types uniform criteria. International Journal of Recent Technology and Engineering, 8(2S11), 3784-3786.20.Abdi H., Williams L. J. Principal component analysis //Wiley Interdisciplinary Reviews: Computational Statistics. -2010. -V. 2, No. 4. -S. 433-459.21.Geurts P., Ernst D., Wehenkel L. Extremely randomized trees // Machine learning. -2006. -T. 63, No. 1. -S. 3-42.22.Shavkat, F., Narzillo, M., & Abdurashid, S.(2019). Selection of significant features of objects in the classification data processing. International Journal of Recent Technology and Engineering, 8(2 Special Issue 11), 3790-3794.23.Niyozmatova, N. A., Mamatov, N., Samijonov, A., Rahmonov, E., & Juraev, S. (2020, September). Method for selecting informative and non-informative features. In IOP Conference Series: Materials Science and Engineering (Vol. 919, No. 4, p. 042013). IOP Publishing.24.Samijonov, A., Mamatov, N., Niyozmatova, N. A., Yuldoshev, Y.,& Asraev, M. (2020, September). Gradient method for determining non-informative features on the basis of a homogeneous criterion with a positive degree. In IOP Conference Series: Materials Science and Engineering (Vol. 919, No. 4, p. 042011). IOP Publishing.25.Mamatov, N., Niyozmatova, N. A., Samijonov, A., Juraev, S., & Abdullayeva, B. (2020, September). The choice of informative features based on heterogeneous functionals. In IOP Conference Series: Materials Science and Engineering (Vol. 919, No. 4, p. 042009). IOP Publishing.26.Niyozmatova, N & Mamatov, Narzillo & Samijonov, Abdurashid & Abdukadirov, B & Abdullayeva, B. (2020). Algorithm for determining the coefficients of the interpolation polynomial of Newton with separated differences. IOP Conference Series: Materials Science and Engineering. 862. 042019. 10.1088/1757-899X/862/4/042019.27.Niyozmatova, N & Mamatov, Narzillo & Samijonov, Abdurashid & Mamadalieva, Naibakhon & Abdullayeva, B. (2020). Unconditional discrete optimization of linear-fractional function “-1”-order. IOP Conference Series: Materials Science and Engineering. 862. 042028. 10.1088/1757-899X/862/4/042028.28.Mamatov, Narzillo & Samijonov, Abdurashid & Niyozmatova, N. (2020). Determination of non-informative features based on the analysis of their relationships. Journal of Physics: Conference Series. 1441. 012149. 10.1088/1742-6596/1441/1/012149.29.Fazilov, Shavkat & Mamatov, Narzillo & Samijonov, Abdurashid & Abdullaev, Sh. (2020). Reducing the dimensionality of feature space in pattern recognition tasks. Journal of Physics: Conference Series. 1441. 012139. 10.1088/1742-6596/1441/1/012139.30.Mamatov, N.S., Samijonov, A.N., Yuldoshev, Y., Khusan, R. (2020). Selection the Informative Features on the Basis of Interrelationship of Features. In: Pawar, P., Ronge, B., Balasubramaniam, R., Vibhute, A., Apte, S. (eds) Techno-Societal 2018 . Springer, Cham. https://doi.org/10.1007/978-3-030-16962-6_1331.Mamatov, Narzillo & Samijonov, Abdurashid & Yuldashev, Zokir. (2019). Selection of features based on relationships. Journal of Physics: Conference Series. 1260. 102008. 10.1088/1742-6596/1260/10/102008.32.Fazilov, S., & Mamatov, N.S. (2019). Formation an informative description of recognizable objects. Journal of Physics: Conference Series, 1210.33.R. Brunelli and T. Poggio, “Face recognition: Features versus templates”, IEEE transactions on pattern analysis and machine intelligence, vol. 15, no. 10, pp. 1042–1052, 1993.
Кутилмоқда