|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|138532||2018||10 صفحه PDF||سفارش دهید||5826 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Automation in Construction, Volume 90, June 2018, Pages 178-187
ANNRI integrates the root-mean-square standard deviation (RMSSTD) and artificial neural network (ANN) to cluster a rust image based on its rust intensity or rusting severity. RMSSTD measures the similarity of rust colors on a rust image, and an ANN trained with the results of a human visual rust inspection experiment would generate the optimal number of clusters for rust intensity recognition. Together with a pre-defined rust color spectrum, ANNRI is able to perform human-visual-perception-like rust intensity recognition and screen out background noises. According to the experiments conducted in this study, the proposed ANNRI can discriminate rust intensity much better than the existing methods with a fixed number of clusters.