Tracing the boundaries of materials in transparent vessels using computer vision
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Visual recognition of material boundaries in transparent vessels is valuable for numerous applications. Such recognition is essential for estimation of fill-level, volume and phase-boundaries as well as for tracking of such chemical processes as precipitation, crystallization, condensation, evaporation and phase-separation. The problem of material boundary recognition in images is particularly complex for materials with non-flat surfaces, i.e., solids, powders and viscous fluids, in which the material interfaces have unpredictable shapes. This work demonstrates a general method for finding the boundaries of materials inside transparent containers in images. The method uses an image of the transparent vessel containing the material and the boundary of the vessel in this image. The recognition is based on the assumption that the material boundary appears in the image in the form of a curve (with various constraints) whose endpoints are both positioned on the vessel contour. The probability that a curve matches the material boundary in the image is evaluated using a cost function based on some image properties along this curve. Several image properties were examined as indicators for the material boundary. The optimal boundary curve was found using Dijkstra's algorithm. The method was successfully examined for recognition of various types of phase-boundaries, including liquid-air, solid-air and solid-liquid interfaces, as well as for various types of glassware containers from everyday life and the chemistry laboratory (i.e., bottles, beakers, flasks, jars, columns, vials and separation-funnels). In addition, the method can be easily extended to materials carried on top of carrier vessels (i.e., plates, spoons, spatulas).
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