An adaptable deep learning system for optical character verification in retail food packaging

Fabio De Sousa Ribeiro, Francesco Caliva, Mark Swainson, Kjartan Gudmundsson, Georgios Leontidis, Stefanos Kollias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Retail food packages contain various types of information such as food name, ingredients list and use by dates. Such information is critical to ensure proper distribution of products to the market and eliminate health risks due to erroneous mislabelling. The latter is considerably detrimental to both consumers and suppliers alike. In this paper, an adaptable deep learning based system is proposed and tested across various possible scenarios: A) for the identification of blurry images and/or missing information from food packaging photos. These were captured during the validation process in supply chains; b) for deep neural network adaptation. This was achieved through a novel methodology that utilises facets of the same convolutional neural network architecture. Latent variables were extracted from different datasets and used as input into a Λ-means clustering and Λ-nearest neighbour classification algorithm, to compute a new set of centroids which better adapts to the target dataset's distribution. Furthermore, visualisation and analysis of network adaptation provides insight into how higher accuracy was achieved when compared to the original deep neural network. The proposed system performed very well in the conducted experiments, showing that it can be deployed in real-world supply chains, for automating the verification process, cutting down costs and eliminating errors that could prove risky for public health.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2018
EditorsYannis Manolopoulos, Lazaros Iliadis, Plamen Angelov, Edwin Lughofer
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781538613764
DOIs
Publication statusPublished - 26 Jun 2018
Event11th IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2018 - Rhodes, Greece
Duration: 25 May 201827 May 2018

Publication series

Name2018 IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2018

Conference

Conference11th IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2018
CountryGreece
CityRhodes
Period25/05/1827/05/18

Keywords

  • Adaptation
  • Clustering
  • Convolutional neural networks
  • Deep learning
  • Optical character verification
  • Retail food packages
  • Trained representations

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