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Detection of boundaries of materials stored in transparent vessels isessential for identifying properties such as liquid level and phase boundaries,which are vital for controlling numerous processes in the industry andchemistry laboratory. This work presents a computer vision method foridentifying the boundary of materials in transparent vessels using thegraph-cut algorithm. The method receives an image of a transparent vesselcontaining a material and the contour of the vessel in the image. The boundaryof the material in the vessel is found by the graph cut method. In general themethod uses the vessel region of the image to create a graph, where pixels arevertices, and the cost of an edge between two pixels is inversely correlatedwith their intensity difference. The bottom 10% of the vessel region in theimage is assumed to correspond to the material phase and defined as the graphand source. The top 10% of the pixels in the vessels are assumed to correspondto the air phase and defined as the graph sink. The minimal cut that splits theresulting graph between the source and sink (hence, material and air) is tracedusing the max-flow/min-cut approach. This cut corresponds to the boundary ofthe material in the image. The method gave high accuracy in boundaryrecognition for a wide range of liquid, solid, granular and powder materials invarious glass vessels from everyday life and the chemistry laboratory, such asbottles, jars, Glasses, Chromotography colums and separatory funnels.

Tracing liquid level and material boundaries in transparent vessels using the graph cut computer vision approach