کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5007870 1461702 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Assessment of speckle-pattern quality in digital image correlation based on gray intensity and speckle morphology
ترجمه فارسی عنوان
ارزیابی کیفیت الگوی رنگی در همبستگی تصویر دیجیتال بر اساس شدت خاکستری و مورفولوژی دانه
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی برق و الکترونیک
چکیده انگلیسی


- Speckle-pattern quality measurement is proposed for digital image correlation.
- The proposed measurement utilizes features of gray intensity and speckle morphology.
- The proposed measurement is inversely proportional to the image correlation error.
- The statistical significance is confirmed by evaluating the p-value.

In digital image correlation (DIC), speckle patterns are generated on the surface of a specimen to resolve uniqueness issues. Thus, speckle patterns significantly affect the accuracy of image correlation. To assess the quality of speckle patterns, the standard deviation of gray intensities within each speckle (SDGIS) is introduced as a new metric. On the basis of the cumulative distribution of SDGIS, speckle-pattern quality measurement (ρ) is proposed, which integrates the features of gray intensity and speckle morphology. Twelve speckle patterns are generated by changing the spraying time and nozzle sizes of an airbrush because these are associated with the speckle volume fraction and speckle size, respectively. In addition, three displacement fields are used to investigate the effects of speckle patterns on the accuracy of the DIC results. For the 12 speckle images associated with the three displacement fields, the correlation results demonstrate that the proposed speckle-pattern quality measurement is inversely proportional to the averaged error of the subset method. This is statistically confirmed by evaluating the correlation coefficient and p-value. Furthermore, the error of the subset method is more affected by speckle patterns than the subset size when the subset size is sufficiently large.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Optics and Lasers in Engineering - Volume 91, April 2017, Pages 62-72
نویسندگان
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