A Visual Approach for Detecting Tyre Flaws That Makes Use of The Curvelet Characteristic

S. Suman Rajest; Shynu T; R. Regin*; Steffi. R

doi:10.31149/ijot.v5i4.4264

Authors

S. Suman Rajest Professor, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India.
Shynu T Master of Engineering, Department of Biomedical Engineering, Agni College of Technology, Chennai, Tamil Nadu, India.
R. Regin* Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, India. [email protected]
Steffi. R Assistant Professor, Department of Electronics and Communication, Vins Christian College of Engineering, Tamil Nadu, India.

Vol. 5 No. 4 (2023): International Journal on Orange Technologies

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April 16, 2023

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Automatic flaw identification is a crucial and difficult subject in the realm of industrial quality inspection for many different types of businesses. After the tyres have been manufactured, we use the curvelet transform to do an analysis on each tyre in order to locate imperfections on the tire's outer surface. In this paradigm, deep image features can be learned, and then later used for detection, classification, and retrieval tasks using bigger coefficients in the sub-highest frequency band represented by the curvelet feature. Curvelets are a type of wavelet transform that are used to represent curvelets. We investigate image categorization challenges using deep learning with the goal of applying our findings to practical, real-world applications. The findings of the experiments demonstrate that the method that was developed is capable of accurately locating and segmenting flaws in tyre images.

S. Suman Rajest, Shynu T, R. Regin*, & Steffi. R. (2023). A Visual Approach for Detecting Tyre Flaws That Makes Use of The Curvelet Characteristic. International Journal on Orange Technologies, 5(4), 17–40. https://doi.org/10.31149/ijot.v5i4.4264

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1. Q. Guo, C. Zhang, H. Liu, and X. Zhang, “Defect detection in tire X-ray images using weighted texture dissimilarity,” J. Sens., vol. 2016, pp. 1–12, 2016.
2. R. Wang, Q. Guo, S. Lu, and C. Zhang, “Tire defect detection using fully convolutional network,” IEEE Access, vol. 7, pp. 43502–43510, 2019.
3. A. Kumar, “Computer-vision-based fabric defect detection: A survey,” IEEE Trans. Ind. Electron., vol. 55, no. 1, pp. 348–363, 2008.
4. Y. Zhang, D. Lefebvre, and Q. Li, “Automatic detection of defects in tire radiographic images,” IEEE Trans. Autom. Sci. Eng., vol. 14, no. 3, pp. 1378–1386, 2017.
5. S. Pandya, T. R. Gadekallu, P. K. Reddy, W. Wang and M. Alazab, "InfusedHeart: A Novel Knowledge-Infused Learning Framework for Diagnosis of Cardiovascular Events," in IEEE Transactions on Computational Social Systems, doi: 10.1109/TCSS.2022.3151643.
6. Satyanaga, H. Rahardjo, and Q. Zhai, “Estimation of unimodal water characteristic curve for gap-graded soil,” Soils and Foundations, vol. 57, no. 5, pp. 789–801, 2017.
7. Satyanaga & H. Rahardjo, “Unsaturated shear strength of soil with bimodal soil-water characteristic curve,” Geotechnique, Vol. 69, No. 9, pp. 828-832, 2019.
8. Satyanaga, H. Rahardjo & C.J. Hua, “Numerical simulation of capillary barrier system under rainfall infiltration,” ISSMGE International Journal of Geoengineering Case Histories, Vol 5(1), pp. 43-54, 2019.
9. Satyanaga & H. Rahardjo, “Role of unsaturated soil properties in the development of slope susceptibility map,” Geotechnical Engineering. Vol 175, No 3, pp. 276-288, 2022.
10. S. R. Vadyala, S. N. Betgeri, J. C. Matthews, and E. Matthews, “A review of physics-based machine learning in civil engineering.” Results in Engineering, vol. 13, p. 100316, 2022.
11. S. R. Vadyala, S. N. Betgeri, and N. P. Betgeri, “Physics-informed neural network method for solving one-dimensional advection equation using PyTorch.” Array, vol. 13, p. 100110, 2022.
12. S. R. Vadyala and E. A. Sherer, “Natural Language Processing Accurately Categorizes Indications, Findings and Pathology Reports From Multicenter Colonoscopy (Preprint).” 2021.
13. S. R. Vadyala, S. N. Betgeri, E. A. Sherer, and A. Amritphale, “Prediction of the number of COVID-19 confirmed cases based on K-means-LSTM.” Array, vol. 11, p. 100085, 2021.
14. R. Agarwal and N. Rao, “ML-based classifier for Sloan Digital Sky spectral objects,” Neuroquantology, vol. 20, no. 6, pp. 8329–8358, 2022.
15. R. Agarwal, “Edge Detection in Images Using Modified Bit-Planes Sobel Operator,” 2014, pp. 203–210. doi: 10.1007/978-81-322-1771-8_18.
16. A. Rashi and R. Madamala, “Minimum relevant features to obtain ai explainable system for predicting breast cancer in WDBC,” Int J Health Sci (Qassim), Sep. 2022, doi: 10.53730/ijhs.v6nS9.12538.
17. R. A. A. Agarwal, “Decision Support System designed to detect yellow mosaic in Pigeon pea using Computer Vision,” Design Engineering (Toronto), vol. 8, pp. 832–844, 2021.
18. R. Agarwal, S. Hariharan, M. Nagabhushana Rao, and A. Agarwal, “Weed Identification using K-Means Clustering with Color Spaces Features in Multi-Spectral Images Taken by UAV,” in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Jul. 2021, pp. 7047–7050.
19. R. Senthilkumar, B. G. Geetha, "Asymmetric Key Blum-Goldwasser Cryptography for Cloud Services Communication Security," Journal of Internet Technology, vol. 21, no. 4 , pp. 929-939, Jul.2020.
20. Senthil kumar, R., Geetha, B.G. Signature Verification and Bloom Hashing Technique for Efficient Cloud Data Storage. Wireless Pers Commun 103, 3079–3097,2018.
21. Roja Boina, “Assessing the Increasing Rate of Parkinson's Disease in the US and its Prevention Techniques”, International Journal of Biotechnology Research and Development, 3(1), pp. 1-18, 2022.
22. B. R. Rajagopal, B. Anjanadevi, M. Tahreem, S. Kumar and M. Debnath, and K. Tongkachok, "Comparative Analysis of Blockchain Technology and Artificial Intelligence and its impact on Open Issues of Automation in Workplace," 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022, pp. 288-292.
23. B.R. Rajagopal, E. Kannapiran, A.D. Gupta, M.Momin and D.S.K. Chakravarthy, "The future prospects and challenges of implementing big data in healthcare management using Structural equation model analysis," Bull. Env. Pharmacol. Life Sci., Spl Issue [1] 2022, pp. 1111-1119, 2022.
24. N.P. Krishnam, M.S. Ashraf, B.R. Rajagopal,P.Vats and D.S.K. Chakravarthy and S.M. Rafi, "Analysis Of Current Trends, Advances And Challenges Of Machine Learning (Ml) And Knowledge Extraction: From Ml To Explainable AI," Industry Qualifications The Institute of Administrative Management UK, Vol.58, pp. 54-62, May 2022.
25. A.D.Gupta, S.M. Rafi, B.R. Rajagopal, T.Milton and S.G.Hymlin, "Comparative analysis of internet of things (IoT) in supporting the health care professionals towards smart health research using correlation analysis," Bull.Env.Pharmacol. Life Sci., Spl Issue [1] 2022, pp. 701-708, 2022.
26. S. Dhanush, S.C. Mohanraj, V.S. Sruthi, S Cloudin, F.J. John Joseph, (2022). CODEDJ-Private Permissioned Blockchain Based Digital Wallet with Enhanced Security, IEEE International Conference on Bio-Neuro Informatics Models and Algorithms. IEEE.
27. A.J. John Joseph, F.J. John Joseph, O.M. Stanislaus, and D. Das (2022). Classification methodologies in healthcare, Evolving Predictive Analytics in Healthcare: New AI techniques for real-time interventions, p 55-73. IET.
28. F.J. John Joseph, (2022). IoT Based Aquarium Water Quality Monitoring and Predictive Analytics Using Parameter Optimized Stack LSTM. In 2022 International Conference on Information Technology (InCIT). IEEE
29. F.J. John Joseph, (2023). Time series forecast of Covid 19 Pandemic Using Auto Recurrent Linear Regression. Journal of Engineering Research.
30. V. Pattana-anake, & F. J. John Joseph (2022). Hyper Parameter Optimization of Stack LSTM Based Regression for PM 2.5 Data in Bangkok, in Proceedings of 2022 International Conference on Business and Industrial Research (ICBIR). IEEE
31. Satyanaga & H. Rahardjo, “Stability of unsaturated soil slopes covered with Melastoma Malabathricum in Singapore,” Geotechnical Engineering. Vol 7, No 6, pp. 393-403. 2020.
32. Satyanaga, H. Rahardjo, Z.H. Koh & H. Mohamed. “Measurement of a soil-water characteristic curve and unsaturated permeability using the evaporation method and the chilled-mirror method,” Journal of Zhejiang University-SCIENCE A. Vol 20, No 5, pp. 368-375, 2019.
33. Satyanaga, N. Bairakhmetov, J.R. Kim & S.-W. Moon. “Role of bimodal water retention curve on the unsaturated shear strength,” Applied Sciences. Vol 12, No 3, pp. 1266. 2022
34. Hameed, S. S., Madhavan, S., & Arumugam, T. (2020). Is consumer behaviour varying towards low and high involvement products even sports celebrity endorsed. International Journal of Scientific and Technology Research, 9(3), 4848-4852.
35. Mani, M., Hameed, S. S., & Thirumagal, A. (2019). Impact of Ict Knowledge, Library Infrastructure Facilities on Students’ usage of E-Resources-An Empirical Study. Library Philosophy and Practice (e-journal), 2225.
36. Banerjee, T., Trivedi, A., Sharma, G.M., Gharib, M. and Hameed, S.S. (2022), "Analyzing organizational barriers towards building postpandemic supply chain resilience in Indian MSMEs: a grey-DEMATEL approach", Benchmarking: An International Journal.
37. Arumugam, T., Sethu, S., Kalyani, V., Shahul Hameed, S., & Divakar, P. (2022). Representing Women Entrepreneurs in Tamil Movies. American Journal of Economics and Sociology, 81(1), 115-125.
38. Sugirtha, C. M. R., Hameed, S. S., & Arumugam, T. (2020). The Impact of Organizational Identification and Employee Engagement on Intellectual Capital Assets: An Empirical Study.
39. Hameed, S. S., & Madhavan, S. (2017). Impact of Sports celebrities endorsements on consumer behaviour of low and high Involvement consumer products. XIBA Business Review (XBR), 3(1-2), 13-20.
40. A. R. Yeruva, C. S. L Vijaya Durga, G. B, K. Pant, P. Chaturvedi and A. P. Srivastava, "A Smart Healthcare Monitoring System Based on Fog Computing Architecture," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022, pp. 904-909.
41. A. R. Yeruva, P. Choudhari, A. Shrivastava, D. Verma, S. Shaw and A. Rana, "Covid-19 Disease Detection using Chest X-Ray Images by Means of CNN," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022, pp. 625-631.
42. A. Rana, A. Reddy, A. Shrivastava, D. Verma, M. S. Ansari and D. Singh, "Secure and Smart Healthcare System using IoT and Deep Learning Models," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022, pp. 915-922.
43. K. Sridhar, Ajay Reddy Yeruva, Renjith P N, Asmita Dixit, Aatif Jamshed, and Ravi Rastogi, “Enhanced Machine learning algorithms Lightweight Ensemble Classification of Normal versus Leukemic Cel”, Journal of Pharmaceutical Negative Results, Vol.13, no.SI-9, pp. 496–505, 2022.
44. Nita S. patil, Sanjay M. Patil, Chandrashekhar M. Raut, Amol P. Pande, Ajay Reddy Yeruva, and Harish Morwani, “An Efficient Approach for Object Detection using Deep Learning”, Journal of Pharmaceutical Negative Results, Vol.13, no.SI-9, pp. 563–572, 2022.
45. P. William, M. Shamim, A. R. Yeruva, D. Gangodkar, S. Vashisht and A. Choudhury, "Deep Learning based Drowsiness Detection and Monitoring using Behavioural Approach," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022, pp. 592-599.
46. T. Vinoth Kumar, A. R. Yeruva, S. Kumar, D. Gangodkar, A. L N Rao and P. Chaturvedi, "A New Vehicle Tracking System with R-CNN and Random Forest Classifier for Disaster Management Platform to Improve Performance," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 2022, pp. 797-804.
47. O. Fabela, S. Patil, S. Chintamani and B. H. Dennis, "Estimation of effective thermal conductivity of porous Media utilizing inverse heat transfer analysis on cylindrical configuration," in ASME 2017 International Mechanical Engineering Congress and Exposition, 2017.
48. S. Patil, S. Chintamani, B. Dennis and R. Kumar, "Real time prediction of internal temperature of heat generating bodies using neural network," Thermal Science and Engineering Progress, vol. 23, 2021.
49. S. Patil, S. Chintamani, J. Grisham, R. Kumar and B. H. Dennis, "Inverse Determination of Temperature Distribution in Partially Cooled Heat Generating Cylinder," in ASME 2015 International Mechanical Engineering Congress and Exposition , 2015.
50. Hashem Shatnawi, “Computational Fluid Flow Model for the Development of an Arterial Bypass Graft”, CFD Lett., vol. 14, no. 10, pp. 99-111, Oct. 2022.
51. I. Khalifa, H. Abd Al-glil, and M. M. Abbassy, “Mobile hospitalization,” International Journal of Computer Applications, vol. 80, no. 13, pp. 18–23, 2013.
52. I. Khalifa, H. Abd Al-glil, and M. M. Abbassy, “Mobile hospitalization for Kidney Transplantation,” International Journal of Computer Applications, vol. 92, no. 6, pp. 25–29, 2014.
53. M. M. Abbassy and A. Abo-Alnadr, “Rule-based emotion AI in Arabic Customer Review,” International Journal of Advanced Computer Science and Applications, vol. 10, no. 9, 2019.
54. M. M. Abbassy and W. M. Ead, “Intelligent Greenhouse Management System,” 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), 2020.
55. M. M. Abbassy, “Opinion mining for Arabic customer feedback using machine learning,” Journal of Advanced Research in Dynamical and Control Systems, vol. 12, no. SP3, pp. 209–217, 2020.
56. M. M. Abbassy, “The human brain signal detection of Health Information System IN EDSAC: A novel cipher text attribute based encryption with EDSAC distributed storage access control,” Journal of Advanced Research in Dynamical and Control Systems, vol. 12, no. SP7, pp. 858–868, 2020.
57. M. M. and S. Mesbah, “Effective e-government and citizens adoption in Egypt,” International Journal of Computer Applications, vol. 133, no. 7, pp. 7–13, 2016.
58. M.M.Abbassy, A.A. Mohamed “Mobile Expert System to Detect Liver Disease Kind”, International Journal of Computer Applications, vol. 14, no. 5, pp. 320–324, 2016.
59. R. A. Sadek, D. M. Abd-alazeem, and M. M. Abbassy, “A new energy-efficient multi-hop routing protocol for heterogeneous wireless sensor networks,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 11, 2021.
60. S. Derindere Köseoğlu, W. M. Ead, and M. M. Abbassy, “Basics of Financial Data Analytics,” Financial Data Analytics, pp. 23–57, 2022.
61. W. Ead and M. Abbassy, “Intelligent Systems of Machine Learning Approaches for developing E-services portals,” EAI Endorsed Transactions on Energy Web, p. 167292, 2018.
62. W. M. Ead and M. M. Abbassy, “A general cyber hygiene approach for financial analytical environment,” Financial Data Analytics, pp. 369–384, 2022.
63. W. M. Ead and M. M. Abbassy, “IOT based on plant diseases detection and classification,” 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
64. W. M. Ead, M. M. Abbassy, and E. El-Abd, “A general framework information loss of utility-based anonymization in Data Publishing,” Turkish Journal of Computer and Mathematics Education, vol. 12, no. 5, pp. 1450–1456, 2021.
65. K. Shriram, M. K. Chakravarthi, Y. V. Pavan Kumar, V. B. Kumar, D. John Pradeep and C. P. Reddy, "Acute Decisive Fuzzy Haptic Surface Response System for Tactile Sensitivity," 2022 International Conference on Decision Aid Sciences and Applications (DASA), 2022, pp. 438-442.
66. K. K. Singh Gautam, R. Kumar, P. C. Sekhar, N. M. Kumar, K. Srinivasa Rao and M. K. Chakravarthi, "Machine Learning Algorithms for 5G and Internet-of-Thing (IoT) Networks," 2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), 2022, pp. 1-4.
67. R. Doss, S. Gupta, M. K. Chakravarthi, H. K. Channi, A. V. Koti and P. Singh, "Understand the Application of Efficient Green Cloud Computing Through Micro Smart Grid in Order to Power Internet Data Center," 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022, pp. 336-340.
68. J. Surve, D. Umrao, M. Madhavi, T. S. Rajeswari, S. L. Bangare and M. K. Chakravarthi, "Machine Learning Applications For Protecting The Information Of Health Care Department Using Smart Internet Of Things Appliances -A REVIEW," 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022, pp. 893-898.
69. S. K. UmaMaheswaran, V. K. Nassa, B. P. Singh, U. K. Pandey, H. Satyala and M. K. Chakravarthi, "An Inventory System Utilizing Neural Network in The Prediction of Machine Learning Techniques," 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022, pp. 1087-1091.
70. M. Farman, A. Akgül, M.T. Tekin, M. M. Akram, A. Aqeel , E. E. Mahmoud, I. S. Yahia, “Fractal fractional-order derivative for HIV/AIDS model with Mittag-Leffler kernel”, Alex. Eng. J, vol. 61, no. 12,pp. 10965-10980, April 2022.
71. K.S. Nisar, A. Aqeel, M. Inc, M. Farman, H. Rezazadeh, L. Akinyemi, M.M. Mannan, “Analysis of dengue transmission using fractional order scheme”, Aims Math, vol. 7 no. 5, pp. 8408–8429, May 2022.
72. M.M. Akram, M. Farman, A. Akgül, M. U. Saleem, A. Ahmad, M. Partohaghigh, F. Jarad, “Analysis of HIV/AIDS model with Mittag-Leffler kernel”, Aims Math, vol. 7 no. 7, pp. 13383-13401, July 2022.
73. Al-Abyadh, Mohammed Hasan Ali, and Hani Abdel Hafeez Abdel Azeem. (2022). "Academic Achievement: Influences of University Students’ Self-Management and Perceived Self-Efficacy" Journal of Intelligence 10, no. 3: 55.
74. Abdel Azeem, H.A.H. and Al-Abyadh, M.H.A. (2021), "Self-compassion: the influences on the university students’ life satisfaction during the COVID-19 outbreak", International Journal of Human Rights in Healthcare, ahead-of-print. https://doi.org/10.1108/IJHRH-08-2021-0153
75. Al-Abrat N.A.S., Alabyad M.H.A. (2021) The Extent of Awareness of Faculty Members at Al-bayda University About the Concept of Educational Technology and Their Attitudes Towards It. In: Al-Bakry A.M. et al. (eds) New Trends in Information and Communications Technology Applications. NTICT 2021. Communications in Computer and Information Science, vol 1511. Springer, Cham.
76. ldbyani, A., & Al-Abyadh, M. H. A. (2022). Relationship between Dark Triad, Mental Health, and Subjective Well-being Moderated by Mindfulness: A Study on Atheists and Muslim Students. Islamic Guidance and Counseling Journal, 5(1), 71–87.
77. AbdulKader, H., ElAbd, E., & Ead, W. (2016). Protecting Online Social Networks Profiles by Hiding Sensitive Data Attributes. Procedia Computer Science, 82, 20–27.
78. Fattoh, I. E., Kamal Alsheref, F., Ead, W. M., & Youssef, A. M. (2022). Semantic sentiment classification for covid-19 tweets using universal sentence encoder. Computational Intelligence and Neuroscience, 2022, 1–8.
79. Ead, W. M., Abdel-Wahed, W. F., & Abdul-Kader, H. (2013). Adaptive Fuzzy Classification-Rule Algorithm In Detection Malicious Web Sites From Suspicious URLs. Int. Arab. J. E Technol., 3, 1–9.
80. Abdelazim, M. A., Nasr, M. M., & Ead, W. M. (2020). A survey on classification analysis for cancer genomics: Limitations and novel opportunity in the era of cancer classification and Target Therapies. Annals of Tropical Medicine and Public Health, 23(24).
81. Alsheref, F. K., Fattoh, I. E., & M.Ead, W. (2022). Automated prediction of employee attrition using ensemble model based on machine learning algorithms. Computational Intelligence and Neuroscience, 2022, 1–9.
82. B Bisoyi, D Das, PS Subbarao, B Das, “An Evaluation on Green Manufacturing: It’s Technique, Significance and Rationality”, IOP Conference Series: Materials Science and Engineering, 653 (1), 012032, 2019.
83. PPS Subbarao, “Bank credit to infrastructure in India – Issues, Challenges and Strategies”, International Research Journal of Commerce & Behavioral Science, 4 (10) 6,2015.
84. PS Subbarao, “Participative Management in Post Liberalization-A Case study of Indian Jute Industry”, International Journal of Decision Making in Management, 2 (1), 55-62, 2013.
85. PS Subbarao, PS Rani, “Application of information Technology in Agriculture-An Indian Experience” European Journal of Business and Management 4 (8), 37-46, 2012.
86. PS Subbarao, PS Rani, “International Technology Transfer to India an Impedimenta & Impetuous,” Global Journal of Business Management, 5 (1), 1-19, 2011.
87. SS Pasumarti, “Accomplishment of Gandhian Globalization Is A Myth or Reality”, Journal of Advanced Research in Dynamical & Control Systems, 11 (6), 52-61, 2019.
88. SS Pasumarti, “CSR and Socio-Economic Development–A case study of selected PSU’s in the State of Odisha” Journal of Critical Reviews, 7 (13), 1407-1415, 2020.
89. SS Priscila, M Hemalatha, “Improving the performance of entropy ensembles of neural networks (EENNS) on classification of heart disease prediction”, Int J Pure Appl Math 117 (7), 371-386, 2017.
90. S Silvia Priscila, M Hemalatha, “ Diagnosisof heart disease with particle bee-neural network” Biomedical Research, Special Issue, pp. S40-S46, 2018.
91. S Silvia Priscila, M Hemalatha, “ Heart Disease Prediction Using Integer-Coded Genetic Algorithm (ICGA) Based Particle Clonal Neural Network (ICGA-PCNN)”, Bonfring International Journal of Industrial Engineering and Management Science 8 (2), 15-19, 2018.