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Classification of dried vegetables using computer image analysis and artificial neural networks

机译:使用计算机图像分析和人工神经网络进行干蔬菜的分类

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In the recent years, there has been a continuously increasing demand for vegetables and dried vegetables. This trend affects the growth of the dehydration industry in Poland helping to exploit excess production. More and more often dried vegetables are used in various sectors of the food industry, both due to their high nutritional qualities and changes in consumers' food preferences. As we observe an increase in consumer awareness regarding a healthy lifestyle and a boom in health food, there is also an increase in the consumption of such food, which means that the production and crop area can increase further. Among the dried vegetables, dried carrots play a strategic role due to their wide application range and high nutritional value. They contain high concentrations of carotene and sugar which is present in the form of crystals. Carrots are also the vegetables which are most often subjected to a wide range of dehydration processes; this makes it difficult to perform a reliable qualitative assessment and classification of this dried product. The many qualitative properties of dried carrots determining their positive or negative quality assessment include colour and shape. The aim of the research was to develop and implement the model of a computer system for the recognition and classification of freeze-dried, convection-dried and microwave vacuum dried products using the methods of computer image analysis and artificial neural networks.
机译:近年来,对蔬菜和干蔬菜需求不断增加。这一趋势影响波兰脱水行业的增长,帮助利用过量生产。越来越多的干燥蔬菜用于食品工业的各个部门,既由于其高营养品质和消费者食物偏好的变化而导致。随着我们观察到有关健康生活方式的消费者意识和健康食品的繁荣,这些食物的消费量也有所增加,这意味着生产和作物面积可以进一步增加。在干燥的蔬菜中,干燥的胡萝卜由于它们的应用范围广泛和高营养价值而起到战略作用。它们含有高浓度的胡萝卜素和糖,其以晶体的形式存在。胡萝卜也是最常见于各种脱水过程的蔬菜;这使得难以进行这种干燥产品的可靠性评估和分类。干燥胡萝卜的许多定性特性确定它们的正面或负质量评估包括颜色和形状。该研究的目的是通过计算机图像分析和人工神经网络的方法,开发和实施用于识别和分类的计算机系统的模型,用于识别和分类干燥,对流干燥和微波真空干燥产品。

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