Abstract: The advances in the classification of individual cooking ingredients are sparse. The problem is that there are almost no public edited records available. This work deals with the problem of automated recognition of a photographed cooking dish and the subsequent output of the appropriate recipe. The distinction between the difficulty of the chosen problem and previous supervised classification problems is that there are large overlaps in food dishes (aka high intra-class similarity), as dishes of different categories may look very similar only in terms of image information. The combination of object recognition or cooking court recognition using Convolutional Neural Networks (short CNN) and the search for the nearest neighbours (Next-Neighbour Classification).

Keywords: Inverse cooking, Image processing, Food recognition, Deep learning, Text generation

PDF | DOI: 10.17148/IJARCCE.2022.11784

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