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Automatic analysis of 2D foam sequences: Application to the characterization of aqueous proteins foams stability

机译:二维泡沫序列的自动分析:用于表征水性蛋白质泡沫的稳定性

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Aqueous foams occur in several industrial applications including food production. One of the challenging issues in foams study is to evaluate the air bubbles stability. This problem is addressed in the present work using sequences of 2D macroscopic images of aqueous foams carried out in a glass column.rnDespite commercial softwares that are currently used in microscopy, the automatic analysis of foam sequences is still an unsolved problem. It can be related to two fundamental problems in the field of image analysis: the granulometric analysis and the automatic tracking of objects in image sequences. Rather than an adaptation of existing granulometric or tracking methods, the proposed foam analyzer consists in a new algorithm based on a double tracking of the foam bubbles: a scale-space tracking, where the scale parameter is the size, and a temporal tracking. It ensures a complete description of any bubble through the time and the detection of any bubbles interaction so that the foam's structure is finally entirely and very precisely described.rnThe proposed foam analyzer has been validated by comparing the characteristics computed by the automatic method to those that can be predicted via the foams physical properties.
机译:水性泡沫出现在包括食品生产在内的多种工业应用中。泡沫研究中的挑战性问题之一是评估气泡的稳定性。在当前工作中,使用在玻璃柱中进行的水性泡沫的2D宏观图像序列解决了这个问题。尽管目前在显微镜检查中使用了商业软件,但泡沫序列的自动分析仍未解决。它可能与图像分析领域中的两个基本问题有关:粒度分析和图像序列中对象的自动跟踪。提出的泡沫分析仪不是对现有的粒度或跟踪方法进行改编,而是基于一种基于泡沫气泡双重跟踪的新算法:比例尺空间跟踪(比例参数为大小)和时间跟踪。它可以确保对整个时间内的气泡进行完整的描述,并检测到气泡之间的相互作用,从而最终完全准确地描述了泡沫的结构。建议的泡沫分析仪已通过将自动方法计算出的特性与那些通过比较自动方法得出的特性进行了验证。可以通过泡沫的物理特性来预测。

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