Abstract
Abstract The paper presents an automatic method for segmenting 3D tomography images of a funnel flow area, during silo emptying process. For generating 3D images the silo model was scanned using X-ray Computed Tomography (CT) system. The method has been applied for a chosen single slice from 3D image. The image segmentation is based on the variance of pixels calculation in defined interrogation window (or kernel). The analysis of Signalto- Noise-Ratio (SNR) of the given image allows to improve the contrast in the image and facilitate the detection the boundary between funnel area and stagnant zone. The obtained results of image segmentation show a high potential in the silo flow investigation using in-situ experiment using X-ray visualization. Additionally, the study indicates that, the separation of the silo area into the funnel and stagnant zone parts is a very challenging task especially for the top and bottom area of silo where the contrast is the smallest.
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