Defect Classification and Detection on Grinding Shaft using Digital Image Processing Process with A-KAZE Features

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Udomsak Wongkong
Sutthithep Sukwiboon
Phlai Chansom
Thossaporn Kaewwichit


This study presents the classification and detection of surface defection on the grinding shaft with two different types of defection: scratch and spot. To detect the defection, digital image processing process with A-KAZE features were applied to stitch the shaft image. To classify the defections, a circular factor is proposed to classify the scratch and the spot. In this study, the circular factors were set at <0.8 for scratch and ≥0.8 for spot. The experimental result report that the circular factors can classify the two detections. In addition, the A-KAZE features which are applied for image stitching indicates 63.32% of overlay image ratio.


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How to Cite
U. . Wongkong, S. . Sukwiboon, P. . Chansom, and T. . Kaewwichit, “Defect Classification and Detection on Grinding Shaft using Digital Image Processing Process with A-KAZE Features”, DTAJ, vol. 2, no. 6, pp. 106–115, Dec. 2020.
Research Articles


Rosati, G., Boschetti, G., Biondi, A., & Rossi, A., “Real-time defect detection on highly reflective curved surfaces”, Optics and Lasers in Engineering, 47 (3-4), 2009, pp. 379-384.

Ali, M., Mailah, M., Kazi, S., & Tang, H. H., “Defects Detection of Cylindrical Object's Surface Using Vision System”, in The 10th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (CIMMACS'11), Jakarta, 2011, pp. 1-3.

Ali, M. A., Mailah, M., Tang, H. H., & Kazi, S., “Visual inspection of cylindrical product’s lateral surface using cameras and image processing”,

International Journal of Mathematical Models and Methods in Applied Sciences, 6(2), 2012, pp. 340-348.

Manish, R., Venkatesh, A., & Ashok, S. D., “Machine vision based image processing techniques for surface finish and defect inspection in a grinding process”, Materials Today: Proceedings, 5(5), 2018, pp. 12792-12802.

Tian, H., Wang, D., Lin, J., Chen, Q., & Liu, Z., “Surface Defects Detection of Stamping and Grinding Flat Parts Based on Machine Vision”,

Sensors, 20 (16), 2020, p. 4531.

Alcantarilla, P. F., & Solutions, T., “Fast explicit diffusion for accelerated features in nonlinear scale spaces”, IEEE Trans. Patt. Anal. Mach. Intell, vol. 34 (7), 2011, pp. 1281-1298.

Andersson, O., & Reyna Marquez, S., “A comparison of object detection algorithms using unmanipulated testing images: Comparing SIFT,


Sharma, S. K., & Jain, K., “Image Stitching using AKAZE Features”, Journal of the Indian Society of Remote Sensing, 48 (10), 2020, pp. 1389-1401.

Dissanayake, V., Herath, S., Rasnayaka, S., Seneviratne, S., Vidanaarachchi, R., & Gamage, C., “Quantitative and qualitative evaluation of

performance and robustness of image stitching algorithms”, In 2015 International Conference on Digital Image Computing: Techniques and

Applications (DICTA), IEEE, 2015, pp. 1-6.

Alcantarilla, P. F., Bartoli, A., & Davison, A. J., “KAZE features”, In European Conference on Computer Vision, Springer, Berlin, Heidelberg, 2012, pp. 214-227.