Machine vision digital technology for non-contact quality control of garment manufacturing

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Despite many years of automation experience, the final inspection stage has not yet been digitized. At sewing enterprises, traditionally, the detection of defects in batches of finished clothes is carried out by contact method by the employees of the technical control department. The aim of the study is to develop a method for recognizing technological and design defects that reduce the grade of products for remote monitoring of the quality of sewing semi - finished products and finished products using a computer vision software - and - hardware complex. An analysis of the existing methods for identifying visual information has shown that to achieve the task, the Haar cascade classifier can be used, which makes it possible to recognize scanned objects with a high degree of reliability by comparing the characteristics of images with templates. The authors have developed the GarmentScanner software and hardware system, which reads visual information using machine vision, classifies it using the Viola/Jones algorithm based on the calculation of the total brightness of pixels in arbitrary rectangular areas, and performs metric actions. At the current stage of the study, the GarmentScanner software works with photographic images of finished products of flat shapes (t - shirts, shorts). The following attributes were selected as the tested attributes: the coordinates of the base and reference points on the product (in accordance with the model features); the symmetry of the contour; the conformity of the dimensions of a particular model to the reference sample (according to the table of measures). Approbation of GarmentScanner work is carried out at outsourcing sewing enterprises in China, cooperating with Russian design agencies. An additional effect from the use of GarmentScanner was the reduction of conflict situations in production, arising against the background of different interpretations by customers from Russia and outsourcing contractors of the concept of "production quality and its rejection".

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Digitalization, garments, manufacturing quality control, machine vision

Короткий адрес: https://sciup.org/142236073

IDR: 142236073   |   DOI: 10.24412/2079-7958-2022-2-10-18

Список литературы Machine vision digital technology for non-contact quality control of garment manufacturing

  • Schwab, K. (2016), The Fourth Industrial Revolution (Top Business Awards), Eksmo, 138 p.
  • Steger, C., Ulrich, M., Wiedemann, C. (2018), Machine Vision Algorithms and Applications, Weinheim:Wiley-VCH Verlag GmbH & Co, 516 p.
  • Dai, W., Dai, C., Ou, S., Li, J., Das, S. (2017), Very deep convolutional neural networks for raw waveforms, Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing, 2017, pp. 421-425.
  • Hopfield, J. J. (1982), Neural networks and physical systems with emergent collective computational abilities, Proceedings of the National Academy of Sciences of the United States of America, 1982, Vol. 79, Is. 8., pp. 2554-2558.
  • Yosinski, J., Clune, J., Nguyen, A., Fuchs, T., Lipson, H. (2015), Understanding neural networks through deep visualization, Proceedings of International Conference on Machine Learning, Deep Learning Workshop, 2015, p. 12.
  • Brown, L. (1992), A survey of image registration techniques, Proceedings of ACM Computing Surveys, 1992, Vol. 24, № 1, pp. 325-376.
  • NaziL, P., Darshan, K., Ishan, B. (2013), An overview on template matching methodologies and its applications, International Journal of Research in Computer and Communication Technology, 2013, VoL. 2, № 10, p. 988-995.
  • Foresight, D., Pons, J. (2018), Компьютерное зрение. Современный подход, Москва, 2018, 960 p.
  • Viola, P., Jones, M. (2001), Rapid object detection using a boosted cascade of simple features, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001, Vol. 1, pp. 511-518.
  • Шеромова, И. А., Старкова, Г. П., Дремлюга, О. А. (2016), Применение компьютерных технологий при оценке качества ниточных соединений, Современные наукоёмкие технологии. Технические науки, 2016, № 12, с. 299-303.
  • Алибекова, М. И., Белгородский, В. С., Андреева, Е. Г. (2021), Инновационные технологии в эскизном и художественном проектировании объемных форм костюма, Известия высших учебных заведений. Технология текстильной промышленности, 2021, № 3, с. 102-106.
  • Petrosova, I. A., Andreeva, E. G., Guseva, M. A. (2019), The system of selection and sale of ready-to-wear clothes in a virtual environment, International Science and Technology Conference "EastConf", Vladivostok, Russia, 2019, pp. 1-5. doi: 10.1109/EastConf.2019.8725390.
  • Rogozhina, Iu., Guseva, M., Andreeva, E. (2022), Garment Production Quality Evaluation Using Machine Vision, Proceeding of the International Science and Technology Conference "FarEastCon
  • Sheromova, I. A., Starkova, G. P., DremLyuga, O. A. (2016), Application of computer technologies in assessing the quality of thread connections [Primenenie komp'juternyh tehnoLogij pri ocenke kachestva nitochnyh soedinenij], Modern science-intensive technologies Technical sciences, 2016, № 12, pp. 299-303.
  • ALibekova, M. I., BeLgorodsky, V. S., Andreeva, E. G. (2021), Innovative technologies in sketch and artistic design of three-dimensionaL costume forms [Innovacionnye tehnoLogii v jeskiz-nom i hudozhestvennom proektirovanii obemnyh form kostjuma], Izvestiya Vysshikh Uchebnykh Zavedenii, Seriya Teknologiya Tekstil-noi Promyshlennosti, 2021, № 3, pp. 102-106.
  • Petrosova, I. A., Andreeva, E. G., Guseva, M. A. (2019), The system of seLection and saLe of ready-to-wear cLothes in a virtuaL environment, International Science and Technology Conference "EastConf", Vladivostok, Russia, 2019, pp. 1-5. doi: 10.1109/EastConf.2019.8725390.
  • Rogozhina, Iu., Guseva, M., Andreeva, E. (2022), Garment Production OuaLity Evaluation Using Machine Vision, Proceeding of the International Science and Technology Conference "FarEastCon 2021". Smart Innovation, Systems and Technologies, 2019, vol. 275, Springer, Singapore. https://doi. org/10.1007/978-981-16-8829-4_27
  • Гусева, М. А., Гетманцева, В. В., Андреева, Е. Г, Рогожина, Ю. В., Смирнов, В. Б. (2020), Цифро-визация дефектов одежды для оптимизации аутсорсингового изготовления «Fast Fashion» коллекций, Дизайн и технологии, 2020, № 75 (117), с. 36-44.
  • Рогожина, Ю. В., Гусева, М. А., Андреева, Е. Г., Белгородский, В. С., Данильченко, А. О., Слободян, М. В. (2021), GarmentScanner, Свидетельство о регистрации программы для ЭВМ № 2021617946 RUS. Опубл. 20.05.2021, бюл. № 5.
  • Рогожина, Ю. В., Гусева, М. А., Андреева, Е. Г., Белгородский, В. С., Глебова, Т. Г. (2020), Базовые цифровые шкалы технологических дефектов швейных изделий, определяемых техническими средствами идентификации, Свидетельство о регистрации базы данных № 2020621712 RUS, опубл. 18.09.2020, бюл. № 9.
  • Гусева, М. А., Рогожина, Ю. В., Андреева, Е. Г., Белгородский, В. С., Глебова, Т. Г. (2020), Цифровые шкалы измерений швейных изделий для автоматизированного контроля качества, Свидетельство о регистрации базы данных № 2020622292 RUS, опубл. 16.11.2020, бюл. № 11.
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