Abstract
In this paper, an alignment approach is proposed for a depth image and a visual image of a tire captured by a laser displacement sensor and a color camera respectively. While the global match usually misaligns the regular textures on a tire, the local match scheme proposed in this paper can exactly locate the logo textures on a tire. The result of the proposed method can be used for defect detection by 2D and 3D texture features. With 2D and 3D texture feature matching, the defect detection will be more accurate.
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References
Zhao, G., Qin, S.: High-precision detection of defects of tire texture through X-ray imaging based on local inverse difference moment features. Sensors 18(8), 191–201 (2018)
Zhang, Y., Lefebvre, D., Li, Q.: Automatic detection of defects in tire radiographic images. IEEE Trans. Autom. Sci. Eng. 14(3), 1378–1386 (2017)
Klimentjew, D., Hendrich, N., Zhang, J.: Multi sensor fusion of camera and 3D laser range finder for object recognition. In: 2010 IEEE Conference on Multisensor Fusion and Integration (2010)
Tuzel, O., Porikli, F., Meer, P.: Region covariance: a fast descriptor for detection and classification. In: European Conference on Computer Vision (ECCV 2006), pp. 589–600 (2006)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Jahne, B., Scharr, H., Korgel, S.: Principles of filter design. In: Computer Vision and Applications, vol. 2, Signal Processing and Pattern Recognition, Chapter 6, pp. 125–151. Academic Press, San Diego (1999)
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Lin, CC., Chang, CC., Chang, CL., Chang, CY. (2020). Fusion Method of Depth Images and Visual Images for Tire Inspection. In: Barolli, L., Nishino, H., Enokido, T., Takizawa, M. (eds) Advances in Networked-based Information Systems. NBiS - 2019 2019. Advances in Intelligent Systems and Computing, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-29029-0_46
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DOI: https://doi.org/10.1007/978-3-030-29029-0_46
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