A non-reference evaluation method for edge detection of wear particles in ferrograph images. (1st February 2018)
- Record Type:
- Journal Article
- Title:
- A non-reference evaluation method for edge detection of wear particles in ferrograph images. (1st February 2018)
- Main Title:
- A non-reference evaluation method for edge detection of wear particles in ferrograph images
- Authors:
- Wang, Jingqiu
Bi, Ju
Wang, Lianjun
Wang, Xiaolei - Abstract:
- Highlights: A non-reference evaluation method for edge detection of wear particles. A quantitative comprehensive index for edge evaluation of ferrograph image. An evaluation sub-index based on reconstruction similarity. Abstract: Edges are one of the most important features of wear particles in a ferrograph image and are widely used to extract parameters, recognize types of wear particles, and assist in the identification of the wear mode and severity. Edge detection is a critical step in ferrograph image processing and analysis. Till date, there has been no single algorithm that guarantees the production of good quality edges in ferrograph images for a variety of applications. Therefore, it is desirable to have a reliable evaluation method for measuring the performance of various edge detection algorithms and for aiding in the selection of the optimal parameter and algorithm for ferrographic applications. In this paper, a new non-reference method for the objective evaluation of wear particle edge detection is proposed. In this method, a comprehensive index of edge evaluation is composed of three components, i.e., the reconstruction based similarity sub-index between the original image and the reconstructed image, the confidence degree sub-index used to show the true or false degree of the edge pixels, and the edge form sub-index that is used to determine the direction consistency and width uniformity of the edges. Two experiments are performed to illustrate the validity ofHighlights: A non-reference evaluation method for edge detection of wear particles. A quantitative comprehensive index for edge evaluation of ferrograph image. An evaluation sub-index based on reconstruction similarity. Abstract: Edges are one of the most important features of wear particles in a ferrograph image and are widely used to extract parameters, recognize types of wear particles, and assist in the identification of the wear mode and severity. Edge detection is a critical step in ferrograph image processing and analysis. Till date, there has been no single algorithm that guarantees the production of good quality edges in ferrograph images for a variety of applications. Therefore, it is desirable to have a reliable evaluation method for measuring the performance of various edge detection algorithms and for aiding in the selection of the optimal parameter and algorithm for ferrographic applications. In this paper, a new non-reference method for the objective evaluation of wear particle edge detection is proposed. In this method, a comprehensive index of edge evaluation is composed of three components, i.e., the reconstruction based similarity sub-index between the original image and the reconstructed image, the confidence degree sub-index used to show the true or false degree of the edge pixels, and the edge form sub-index that is used to determine the direction consistency and width uniformity of the edges. Two experiments are performed to illustrate the validity of the proposed method. First, this method is used to select the best parameters for an edge detection algorithm, and it is then used to compare the results obtained using various edge detection algorithms and determine the best algorithm. Experimental results of various real ferrograph images verify the effectiveness of the proposed method. … (more)
- Is Part Of:
- Mechanical systems and signal processing. Volume 100(2018)
- Journal:
- Mechanical systems and signal processing
- Issue:
- Volume 100(2018)
- Issue Display:
- Volume 100, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 100
- Issue:
- 2018
- Issue Sort Value:
- 2018-0100-2018-0000
- Page Start:
- 863
- Page End:
- 876
- Publication Date:
- 2018-02-01
- Subjects:
- Edge evaluation -- Ferrograph image -- Wear particle analysis -- Edge detection
Structural dynamics -- Periodicals
Vibration -- Periodicals
Constructions -- Dynamique -- Périodiques
Vibration -- Périodiques
Structural dynamics
Vibration
Periodicals
621 - Journal URLs:
- http://www.sciencedirect.com/science/journal/08883270 ↗
http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0888-3270;screen=info;ECOIP ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ymssp.2017.08.014 ↗
- Languages:
- English
- ISSNs:
- 0888-3270
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5419.760000
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