International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 16, No. 2, 8 Apr. 2024
Cover page and Table of Contents: PDF (size: 1364KB)
STEM Project for Vehicle Image Segmentation Using Fuzzy Logic
PDF (1364KB), PP.45-57
Views: 0 Downloads: 0
Author(s)
Serhiy Balovsyak
1
Oleksandr Derevyanchuk
1
Vasyl Kovalchuk
2
Hanna Kravchenko
3
Yuriy Ushenko
1,*
Zhengbing Hu
4
Index Terms
STEM Education, STEM Project, Project-Based Learning (PjBL), Artificial Intelligence in Education, Image Segmentation, Fuzzy Logic
Abstract
A STEM project was implemented, which is intended for students of technical specialties to study the principles of building and using a computer system for segmentation of images of railway transport using fuzzy logic. The project consists of 4 stages, namely stage #1 "Reading images from video cameras using a personal computer or Raspberry Pi microcomputer", stage #2 "Digital image pre-processing (noise removal, contrast enhancement, contour selection)", stage #3 "Segmentation of images", stage #4 "Detection and analysis of objects on segmented images by means of fuzzy logic". Hardware and software tools have been developed for the implementation of the STEM project. A personal computer and a Raspberry Pi 3B+ microcomputer with attached video cameras were used as hardware. Software tools are implemented in the Python language using the Google Colab cloud platform. At each stage of the project, students deepen their knowledge and gain practical skills: they perform hardware and software settings, change program code, and process experimental images of vehicles. It is shown that the processing of experimental images ensures the correct selection of meaningful parts in images of vehicles, for example, windows and number plates in images of locomotives. Assessment of students' educational achievements was carried out by testing them before the start of the STEM project, as well as after the completion of the project. The topics of the test tasks corresponded to the topics of the stages of the STEM project. Improvements in educational achievements were obtained for all stages of the project.
Cite This Paper
Serhiy Balovsyak, Oleksandr Derevyanchuk, Vasyl Kovalchuk, Hanna Kravchenko, Yuriy Ushenko, Zhengbing Hu, "STEM Project for Vehicle Image Segmentation Using Fuzzy Logic", International Journal of Modern Education and Computer Science(IJMECS), Vol.16, No.2, pp. 45-57, 2024. DOI:10.5815/ijmecs.2024.02.04
Reference
[1]Y. Li, Y. Xiao, K. Wang, et al., “A systematic review of high impact empirical studies in STEM education”, International Journal of STEM Education (IJSTEM), vol. 9, no. 72, pp. 1-18, 2022. doi: 10.1186/s40594-022-00389-1.
[2]Y. Li, Y. Xiao, “Authorship and topic trends in STEM education research”, International Journal of STEM Education (IJSTEM), vol. 9, no. 62, pp. 1-7, 2022. doi: 10.1186/s40594-022-00378-4.
[3]V. Kovalchuk, A. Androsenko, А. Boiko, V. Tomash, O. Derevyanchuk, “Development of Pedagogical Skills of Future Teachers of Labor Education and Technology by means of Digital Technologies”, International Journal of Computer Science and Information Security, vol. 22, no. 9, pp. 551-560, 2022. doi: 10.22937/IJCSNS.2022.22.9.71.
[4]Thiago Nascimento Rodrigues, "A Fast Topological Parallel Algorithm for Traversing Large Datasets", International Journal of Information Technology and Computer Science, Vol.15, No.1, pp.1-8, 2023.
[5]Nikita Taneja, Hardeo Kumar Thakur, "Evaluating the Scalability of Matrix Factorization and Neighborhood Based Recommender Systems", International Journal of Information Technology and Computer Science, Vol.15, No.1, pp.21-29, 2023.
[6]Sun Fayou, Hea Choon Ngo, Yong Wee Sek, “Combining Multi-Feature Regions for Fine-Grained Image Recognition”, International Journal of Image, Graphics and Signal Processing, vol. 14, no. 1, pp. 15-25, 2022.
[7]DaeEun Kim, Dosik Hwang, Intelligent Imaging and Analysis. Switzerland, Basel: MDPI, 2020.
[8]R. Gonzalez, R. Woods, Digital image processing. 4th edidion, Pearson/ Prentice Hall, NY, 2018.
[9]A. R. Fayek, “Fuzzy Logic and Fuzzy Hybrid Techniques for Construction Engineering and Management”, Journal of Construction Engineering and Management, vol. 146, no. 7, pp. 1-12, 2020. doi: 10.1061/(ASCE)CO.1943-7862.0001854.
[10]W. Xu, F. Ouyang, “The application of AI technologies in STEM education: a systematic review from 2011 to 2021”, International Journal of STEM Education (IJSTEM), vol. 9, no. 59, pp. 1-20, 2022. doi: 10.1186/s40594-022-00377-5.
[11]Selamat Triono Ahmad, Ronal Watrianthos, Agariadne Dwinggo Samala, Mukhlidi Muskhir, Gimba Dogara, “Project-based Learning in Vocational Education: A Bibliometric Approach”, International Journal of Modern Education and Computer Science (IJMECS), vol. 15, no. 4, pp. 43-56, 2023. doi: 10.5815/ijmecs.2023.04.04.
[12]M.A. Samsudin, S.M. Jamali, A.N. Md Zain, N. Ale Ebrahim, “The Effect of STEM Project Based Learning on Self-Efficacy among High-School Physics Students”, Journal of Turkish Science Education, vol. 17, no. 1, pp. 94-108, 2020. doi: 10.36681/tused.2020.15.
[13]Ihor Tereikovskyi, Zhengbing Hu, Denys Chernyshev, Liudmyla Tereikovska, Oleksandr Korystin, Oleh Tereikovskyi, “The Method of Semantic Image Segmentation Using Neural Networks”, International Journal of Image, Graphics and Signal Processing(IJIGSP), vol. 14, no. 6, pp. 1-14, 2022. doi: 10.5815/ijigsp.2022.06.01
[14]Tarik Bourahi, Azouazi Mohamed, Abdessamad Belangour. “The application of fuzzy logic to improve orientation in system education in Morocco”, Journal of Theoretical and Applied Information Technology, vol. 99, no. 13, pp. 3292-3305, 2021.
[15]Tengku Zatul Hidayah Tengku Petra, Mohd Juzaiddin Ab Aziz, “Analysing Student Performance in Higher Education Using Fuzzy Logic Evaluation”, International journal of scientific & technology research, vol. 10, no. 01, pp. 322-327, 2021.
[16]S.V. Balovsyak, Kh. S. Odaiska, “Automatic Determination of the Gaussian Noise Level on Digital Images by High-Pass Filtering for Regions of Interest”, Cybernetics and Systems Analysis, vol. 54, no. 4, pp. 662-670, 2018. doi: 10.1007/s10559-018-0067-3.
[17]S.V. Balovsyak, O.V. Derevyanchuk, I.M. Fodchuk, “Method of calculation of averaged digital image profiles by envelopes as the conic sections”, Advances in Intelligent Systems and Computing, Hu Z., Petoukhov S., Dychka I., He M. (Eds.), Springer International Publishing, vol. 754, pp. 204–212, 2019. doi: 10.1007/978-3-319-91008-6_21.
[18]S.V. Balovsyak, O.V. Derevyanchuk, H.O. Kravchenko, O.P. Kroitor, V.V. Tomash, “Computer system for increasing the local contrast of railway transport images”, Proc. SPIE, Fifteenth International Conference on Correlation Optics, vol. 12126, pp. 121261E1-7, 2021. doi: 10.1117/12.2615761.
[19]S.V. Balovsyak, O.V. Derevyanchuk, Ya.V. Derevianchuk, V.V. Tomash, S.V. Yarema, “Segmentation of railway transport images using fuzzy logic”, Trans Motauto World, vol. 7, no. 3, pp. 122-125, 2022.
[20]Raspberry Pi 3 Model B+. URL: https://www.raspberrypi.org/products/raspberry-pi-3-model-b-plus/.
[21]Google Colab. URL: https://colab.research.google.com.
[22]F. Taşdemir, “Examination of the Effect of STEM Education on Academic Achievement: A Meta-Analysis Study”, Education Quarterly Reviews, vol. 5, no. 2, pp. 282-298, 2022. doi: 10.31014/aior.1993.05.02.489.