Detection of microcracks in silicon solar cells using Otsu-Canny edge detection algorithm

Monicka, S. Gayathri; Manimegalai, D.; Karthikeyan, M.

doi:10.1016/j.ref.2022.09.002

Cited by 16 publications

(7 citation statements)

References 19 publications

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“…Although the primary focus of the study is to contrast the PCS method with the traditional weighted sum method, an additional experiment was conducted to compare the PCS method with another grayscaling method for verification. Otsu’s method was used as an alternative edge defect detection method in comparison to the PCS method [ 43 , 44 , 45 ]. The results of this extended comparison are listed in Table 6 , alongside the results of the PCS and weighted sum methods.…”

Section: Resultsmentioning

confidence: 99%

“…Although the primary focus of the study is to contrast the PCS method with the traditional weighted sum method, an additional experiment was conducted to compare the PCS method with another grayscaling method for verification. Otsu's method was used as an alternative edge defect detection method in comparison to the PCS method [43][44][45]. As shown in Figure 11, the blue line indicates the guideline, representing the edge of the film, while the red line represents the measured line that distinguishes the coated and noncoated areas.…”

Section: Resultsmentioning

confidence: 99%

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Image Data-Centric Visual Feature Selection on Roll-to-Roll Slot-Die Coating Systems for Edge Wave Coating Defect Detection

Lee,

Yun,

Lee

et al. 2024

Polymers

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Roll-to-roll (R2R) manufacturing depends on a system’s capability to deposit high-quality coatings with precise thickness, width, and uniformity. Therefore, consistent maintenance requires the immediate and accurate detection of coating defects. This study proposes a primary color selection (PCS) method to detect edge defects in R2R systems. This method addresses challenges associated with training data demands, complexity, and defect adaptability through a vision data-centric approach, ensuring precise edge coating defect detection. Using color information, high accuracy was achieved while minimizing data capacity requirements and processing time. Precise edge detection was facilitated by accurately distinguishing coated and noncoated regions by selecting the primary color channel based on color variability. The PCS method achieved superior accuracy (95.8%), outperforming the traditional weighted sum method (78.3%). This method is suitable for real-time detection in manufacturing systems and mitigates edge coating defects, thus facilitating quality control and production optimization.

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Section: Resultsmentioning

confidence: 99%

“…Although the primary focus of the study is to contrast the PCS method with the traditional weighted sum method, an additional experiment was conducted to compare the PCS method with another grayscaling method for verification. Otsu's method was used as an alternative edge defect detection method in comparison to the PCS method [43][44][45]. As shown in Figure 11, the blue line indicates the guideline, representing the edge of the film, while the red line represents the measured line that distinguishes the coated and noncoated areas.…”

Section: Resultsmentioning

confidence: 99%

Image Data-Centric Visual Feature Selection on Roll-to-Roll Slot-Die Coating Systems for Edge Wave Coating Defect Detection

Lee,

Yun,

Lee

et al. 2024

Polymers

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show abstract

“…It also can be seen from Table 6 that the introduction of polarization thermal imaging can significantly improve the detection accuracy, whose error rate compared with infrared thermography is down as much as 21.8%, 17.6%, 31.4%, and 22.2% in the hollowing defect areas of the circle, rectangle, triangle, and square under the same experimental treatments. (2) In order to verify the superiority of the improved Canny algorithm proposed in this paper in extracting the contours of building hollowing defects using polarization thermal images, the performances of the Roberts, Sobel, Prewitt, Log [48], Canny, and the output contour size with pixel area method [49] algorithms were compared with each other. The six detection algorithms lead to different errors between the processing results and the actual sizes, and the output edge detection results of hollowing defects processed using these algorithms and the morphological processing results of corresponding images are shown in Figures 11 and 12 After the integrated comparison of the edge detection results of polarization thermal images of hollowing using several methods, it can be found that, as shown in Figure 11a,c,d, the true edge points of hollowing defects extracted using the Roberts, Prewitt, and Log algorithms are missing to varying degrees, with the most severe edge feature loss of hollowing defects in the images processed using the Prewitt algorithm.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

A Method for Extracting Contours of Building Facade Hollowing Defects Using Polarization Thermal Images Based on Improved Canny Algorithm

Zhu,

Li,

Wang

et al. 2023

Buildings

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During the service process of high-rise buildings, hollowing defects may be produced in the decorative layer, which not only affect the appearance, but also create a safety hazard of wall covering and shattered plaster peeling. Numerous studies have shown that hollowing can be detected using infrared thermal imagery under normal conditions. However, it is difficult to detect the edge and calculate the area of the hollowing on an exterior facade accurately because of the low contrast and fuzzy boundaries of the obtained infrared thermal images. To address these problems, a method for extracting the contours of building facade hollowing defects using polarization thermal images based on an improved Canny algorithm has been proposed in this paper. Firstly, the principle of thermal polarization imaging was introduced for hollowing detection. Secondly, considering the shortcomings of the Canny edge detection algorithm and the features of polarization thermal images, an improved Canny edge detection algorithm is proposed, including adaptive bilateral filtering to improve noise reduction ability while ensuring defect edges are not virtualized, Laplacian sharpening and histogram equalization to achieve contour sharpening and contrast enhancement, and eight-direction gradient templates for calculating image gradients, which make interpolation with non-maximum suppression more accurate, and the Tsallis entropy threshold segmentation algorithm based on the OTSU algorithm verification makes the image contour information more complete and accurate. Finally, a long-wave infrared polarization thermal imaging experimental platform was established and validation experiments were conducted. The experimental results demonstrate that the distinct, smooth, and precise location edges of the hollowing polarization infrared thermal images can be obtained, and the average error of the detected hollowing area is about 10% using the algorithm proposed in this paper.

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“…In addition, SAR images of SGLs are influenced by the topography and surface environment, which cause each individual lake to have different boundary characteristics in SAR. To overcome the regional environmental differences for each SGL extraction, the OCO method introduces the Otsu-Canny edge detection algorithm [28,29] to the Canny edge Otsu algorithm. The Otsu-Canny edge detection algorithm uses the Otsu threshold to complete the segmentation of automatic thresholds, thereby overcoming the subjective dual-threshold settings in Canny edge detection [30].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Supraglacial Lake Distribution and Full-Year Changes Using Multisource Time-Series Satellite Imagery

Zhu,

Zhou,

Zhu

et al. 2023

Remote Sensing

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Change of supraglacial lakes (SGLs) is an important hydrological activity on the Greenland ice sheet (GrIS), and storage and drainage of SGLs occur throughout the year. However, current studies tend to split SGL changes into melt/non-melt seasons, ignoring the effect of buried lakes in the exploration of drainage, and the existing threshold-based approach to SGL extraction in a synthetic aperture radar (SAR) is influenced by the choice of the study area mask. In this study, a new method (Otsu–Canny–Otsu (OCO)), which accesses the features of SGLs on optical and SAR images objectively, is proposed for full-year SGL extraction with Google Earth Engine (GEE). The SGLs on the Petermann Glacier were monitored well by OCO throughout 2021, including buried lakes and more detailed rapid drainage events. Some SGLs’ extent varied minimally in a year (area varying by 10–25%) while some had very rapid drainage (a rapid drainage event from July 26 to 30). The SGL extraction results were influenced by factors such as the mode of polarization, the surface environment, and the depth of the lake. The OCO method can provide a more comprehensive analysis for SGL changes throughout the year.

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Detection of microcracks in silicon solar cells using Otsu-Canny edge detection algorithm

Cited by 16 publications

References 19 publications

Image Data-Centric Visual Feature Selection on Roll-to-Roll Slot-Die Coating Systems for Edge Wave Coating Defect Detection

Image Data-Centric Visual Feature Selection on Roll-to-Roll Slot-Die Coating Systems for Edge Wave Coating Defect Detection

A Method for Extracting Contours of Building Facade Hollowing Defects Using Polarization Thermal Images Based on Improved Canny Algorithm

Monitoring of Supraglacial Lake Distribution and Full-Year Changes Using Multisource Time-Series Satellite Imagery

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