ArticleSensors (Basel, Switzerland)2016
Gap Measurement of Point Machine Using Adaptive Wavelet Threshold and Mathematical Morphology.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 26 citations in OpenAlex.
- An Adaptive Transmitting Scheme for Interrupted Sampling Repeater Jamming Suppression.Sensors (Basel, Switzerland) · 2017Article
- Evaluating Degradation at Railway Crossings Using Axle Box Acceleration Measurements.Sensors (Basel, Switzerland) · 2017Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
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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.
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