SURFACE DEFECT DETECTION WITH MACHINE LEARNING

Prema N S; Shamitha Raj; Prashanth M V; Scinchana S Kumar; Rinla C Mary; Yashwanth S

SURFACE DEFECT DETECTION WITH MACHINE LEARNING

March 2023

Vol-9, Issue-2

Paper ID: 19324

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Surface Defect Machine Learning Classification Random Forest Convolution neural network.

Abstract

A product's surface quality is its most important characteristic. Manual defect inspection is a laborious task in an industry. As a result, it is challenging to provide the certainty of an impeccable steel surface. Machine Learning based automatic surface investigation strategies have emerged as a highly effective and popular solution in recent years to suit customer requirements, speed up the inspection process, and increase the industry's overall efficiency. To overcome this issue, we used a conventional machine learning strategy. With the help of image preprocessing techniques, this project aims to improve the model's performance. It then trains and creates a machine learning model to segment and categorize faulty images using the features that were extracted. The NEU provided the input. The NEU surface defect database serves as the source of the input. Six different forms of flaws are included in this database: crazing, inclusion, patches, pitted surfaces, rolled-in scale, and scratches to divide and organize photos of defects.

License

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Author Information

#	Name	Institute / Affiliation
1	Prema N S	Department of Information Science Engineering Vidyavardhaka College of Engineering Mysuru,INDIA
2	Shamitha Raj	Department of Information Science Engineering Vidyavardhaka College of Engineering Mysuru,INDIA
3	Prashanth M V	Department of Information Science Engineering Vidyavardhaka College of Engineering Mysuru,INDIA
4	Scinchana S Kumar	Department of Information Science Engineering Vidyavardhaka College of Engineering Mysuru,INDIA
5	Rinla C Mary	Department of Information Science Engineering Vidyavardhaka College of Engineering Mysuru,INDIA
6	Yashwanth S	Department of Information Science Engineering Vidyavardhaka College of Engineering Mysuru,INDIA

How to Cite

Use the following formats to cite this article in your research.

APA Style

S, Prema N, Raj, Shamitha, V, Prashanth M, Kumar, Scinchana S, Mary, Rinla C, & S, Yashwanth (2023). SURFACE DEFECT DETECTION WITH MACHINE LEARNING. International Journal of Advance Research and Innovative Ideas In Education, 9(2), 92-96.

MLA Style

S, Prema N, et al. "SURFACE DEFECT DETECTION WITH MACHINE LEARNING." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, 2023, pp. 92-96.

IEEE Style

Prema N S, Shamitha Raj, Prashanth M V, Scinchana S Kumar, Rinla C Mary, and Yashwanth S, "SURFACE DEFECT DETECTION WITH MACHINE LEARNING," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, pp. 92-96, 2023.

Vancouver Style

S Prema N, Raj Shamitha, V Prashanth M, Kumar Scinchana S, Mary Rinla C, S Yashwanth. SURFACE DEFECT DETECTION WITH MACHINE LEARNING. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(2):92-96.

Harvard Style

S, Prema N, Raj, Shamitha, V, Prashanth M, Kumar, Scinchana S, Mary, Rinla C, & S, Yashwanth (2023) 'SURFACE DEFECT DETECTION WITH MACHINE LEARNING', International Journal of Advance Research and Innovative Ideas In Education, 9(2), pp. 92-96.

Chicago Style

S, Prema N, et al. "SURFACE DEFECT DETECTION WITH MACHINE LEARNING." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 92-96.

Turabian Style

S, Prema N, et al. "SURFACE DEFECT DETECTION WITH MACHINE LEARNING." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 92-96.