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Automated labeling method for direction detection of objects inside X-ray image
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- Authors
- Jungi Lee, HyunYong Lee, Nac-Woo Kim, Yumin Hwang, Seok-Kap Ko
- Issue Date
- 2023-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2023, pp.1358-1360
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- To utilize image datasets for deep learning models, high-quality labeling data is required for good performance. In the case of acquiring a dataset, there are difficulties such as making an annotation by manpower. Many studies or software are provided to increase the convenience of such labeling. In this paper, YOLOX-based object detection, Canny edge detection, and Hough transformation-based linear component extraction techniques are applied to automatically label the position of a linear structure inside an X-ray image. To verify this method, actually acquired X-ray images of wind turbine blades were used in this experiment.
- KSP Keywords
- Canny Edge Detection, Component extraction, Direction detection, Extraction technique, High-quality, Hough transformation, Labeling method, Wind turbine blades, X-ray images, deep learning(DL), deep learning models