Segmentation of shallow scratches image using an improved multi-scale line detection approach

Jiang, Xiaoliang; Yang, Xiaojun; Ying, Zhengen; Zhang, Liwen; Pan, Jie; Chen, Shaojie

doi:10.1007/s11042-018-6222-z

Cited by 7 publications

(3 citation statements)

References 31 publications

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“…In the pursuit of a more comprehensive quantitative appraisal of the detection methodology posited in this study, a series of batch experiments were conducted upon a dataset encompassing 30 defective brake disc samples and 100 compliant samples, thereby resulting in a total sample population of 130 brake disc specimens. Selecting A: the detection methods mentioned in [39], B: the detection methods mentioned in [40], and C: the algorithm used in this study before improvement, and comparing them with D: the improved algorithm in this study, which combines the Canny operator with the probabilistic Hough transform for scratch connection in experimental evaluation. To ensure the consistency of comparative experiments, any processing steps not explicitly mentioned in the literature were uniformly handled according to the corresponding steps in our research methodology.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Brake disc positioning and defect detection method based on improved Canny operator

Guo,

Yang,

Xiong

et al. 2024

IET Image Processing

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Firstly, the Canny operator combined with circle fitting is used to position the working surface. Secondly, the median filter and the Laplacian operator are selected for preprocessing. Due to uneven illumination, surface texture, or environmental dust, the extracted scratches exhibit fragmentation, and traditional morphological operations cannot handle scratches well, so an improved Canny operator combined with probabilistic Hough transform is proposed for scratch connection. A bidirectional connection is introduced to optimize the edge detection process of the Canny operator, and a parallel algorithm is introduced to shorten the detection time. Finally, the standard Hough transform needs to traverse the entire parameter space, and the calculation is complicated, and the probability Hough transform is selected. The experimental results show that compared with the traditional Canny algorithm, the precision, recall, and F1‐score of the improved Canny algorithm are increased by 3.2%, 13.2%, and 6.0%, respectively. After adding parallel processing, the average detection time was reduced by 45 ms. Finally, the accuracy of scratches extracted using this algorithm reached 97.96%, the leak rate, and mistake rate of this study are only 3.33% and 2.00%, which provides a more accurate and efficient theoretical support for the research on brake disc scratch detection.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Brake disc positioning and defect detection method based on improved Canny operator

Guo,

Yang,

Xiong

et al. 2024

IET Image Processing

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show abstract

“…In order to solve this problem, researchers have done a lot of work [4][5][6]. In machine vision technology, scratch detection has been addressed mainly in the field of image processing by utilizing an optical microscope under good lighting conditions [7][8][9][10][11][12][13], Convolutional Neural Networks (CNN) [14][15][16], and mathematical morphology [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

“…The proposed edge detection method based on a two-dimensional (2D)-direction filter and a modified adaptive threshold method was used to automatically detect the edge of the scratches on a filtered image [17]. A multi-scale line detection method was used to efficiently extract shallow scratches [18]. Morphological operations with arc-shaped SEs were proposed without polar transformation, which can achieve high detection accuracy for various small defects, including scratches, bumps, and edge bursts [19].…”

Section: Introductionmentioning

confidence: 99%

Image-Based Scratch Detection by Fuzzy Clustering and Morphological Features

Tan

Fei

et al. 2020

Applied Sciences

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Detection of scratch defects on randomly textured surfaces remains challenging due to their unnoticeable visual features. In this paper, an algorithm for piezoelectric ceramic plate surface scratch defects based on the combination of fuzzy c-means clustering and morphological features is proposed. Foreground membership of each gray value is calculated firstly on a reference set of training images by fuzzy c-means clustering and the interpolation method, then an enhanced image is obtained by multiplying the foreground membership function and gray image. The location relationship between regions and the gradient direction of regions is extracted from the binary image of the enhanced image. Based on the morphological features, isolated non-scratched defects are filtered out and the intermittent scratches are merged. Experiments show that the algorithm can be used to detect scratch defects on the surface of a piezoelectric ceramics plate with randomly textured surfaces.

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Intelligent System for Determining the Presence of Falsification in Meat Products Based on Histological Methods

Большаков

Nikitina

Kalimullina

2021

Society 5.0: Cyberspace for Advanced Human-Centered Society

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Segmentation of shallow scratches image using an improved multi-scale line detection approach

Cited by 7 publications

References 31 publications

Brake disc positioning and defect detection method based on improved Canny operator

Brake disc positioning and defect detection method based on improved Canny operator

Image-Based Scratch Detection by Fuzzy Clustering and Morphological Features

Intelligent System for Determining the Presence of Falsification in Meat Products Based on Histological Methods

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