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The ability to recognize the liquid surface and the liquid level intransparent containers is perhaps the most commonly used evaluation method whendealing with fluids. Such recognition is essential in determining the liquidvolume, fill level, phase boundaries and phase separation in various fluidsystems. The recognition of liquid surfaces is particularly important insolution chemistry, where it is essential to many laboratory techniques (e.g.,extraction, distillation, titration). A general method for the recognition ofinterfaces between liquid and air or between phase-separating liquids couldhave a wide range of applications and contribute to the understanding of thevisual properties of such interfaces. This work examines a computer visionmethod for the recognition of liquid surfaces and liquid levels in varioustransparent containers. The method can be applied to recognition of bothliquid-air and liquid-liquid surfaces. No prior knowledge of the number ofphases is required. The method receives the image of the liquid container andthe boundaries of the container in the image and scans all possible curves thatcould correspond to the outlines of liquid surfaces in the image. The methodthen compares each curve to the image to rate its correspondence with theoutline of the real liquid surface by examining various image properties in thearea surrounding each point of the curve. The image properties that were foundto give the best indication of the liquid surface are the relative intensitychange, the edge density change and the gradient direction relative to thecurve normal.

Computer vision-based recognition of liquid surfaces and phase boundaries in transparent vessels, with emphasis on chemistry applications