International Joural of User-System Interaction · 2020 · 13 citations · 12 references
ComputingComputer ScienceFood ScienceComputer VisionMachine LearningMachine VisionDeep LearningExpiration DatingOptical Character RecognitionPattern RecognitionSpeech RecognitionDataset DescriptionsDeep Learning DetectionExpiration Date DeterminationFood Waste ManagementNeural Network-based RecognitionPrinted Character RecognitionRefrigerators
This paper proposes a deep learning solution for optical character recognition, specifically tuned to detect expiration dates that are printed on the packaging of food items. This method can be used to reduce food waste, having a significant impact on the design of smart refrigerators and can prove especially useful for persons with vision difficulties, by combining it with a speech synthesis engine. The main problem in designing an efficient solution for expiry date recognition is the lack of a large enough dataset to train deep neural networks. To tackle this issue, we propose to use an additional dataset composed of synthetically generated images. Both the synthetic and real image datasets are detailed in the paper and we show that the proposed method offers a 9.4% accuracy improvement over using real images alone.
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