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- Title
Gap Measurement of Point Machine Using Adaptive Wavelet Threshold and Mathematical Morphology.
- Authors
Tianhua Xu; Guang Wang; Haifeng Wang; Tangming Yuan; Zhiwang Zhong
- Abstract
A point machine's gap is an important indication of its healthy status. An edge detection algorithm is proposed to measure and calculate a point machine's gap from the gap image captured by CCD plane arrays. This algorithm integrates adaptive wavelet-based image denoising, locally adaptive image binarization, and mathematical morphology technologies. The adaptive wavelet-based image denoising obtains not only an optimal denoising threshold, but also unblurred edges. Locally adaptive image binarization has the advantage of overcoming the local intensity variation in gap images. Mathematical morphology may suppress speckle spots caused by reflective metal surfaces in point machines. The subjective and objective evaluations of the proposed method are presented by using point machine gap images from a railway corporation in China. The performance between the proposed method and conventional edge detection methods has also been compared, and the result shows that the former outperforms the latter.
- Subjects
EDGE detection (Image processing); ALGORITHMS; IMAGE denoising; WAVELET transforms; IMAGE processing
- Publication
Sensors (14248220), 2016, Vol 16, Issue 12, p2006
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s16122006