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Product verification using OCR classification and Mondrian conformal prediction
Department of Computing, Jönköping AI Lab, Jönköping University, Sweden.
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. ITAB Shop Products AB, Sweden ; Department of Computing, Jönköping AI Lab, Jönköping University, Sweden. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-8880-7965
Department of Computing, Jönköping AI Lab, Jönköping University, Sweden.
2022 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 188, article id 115942Article in journal (Refereed) Published
Abstract [en]

The retail sector is undergoing an apparent digital transformation that completely revolutionises shopping operations. To stay competitive, retailer stakeholders are forced to rethink and improve their business models to provide an attractive personalised experience to consumers. The self-service checkout process is at the heart of this transformation and should be designed to identify the products accurately and detect any possible anomalous behaviour. In this paper, we introduce a product verification system based on OCR classification and Mondrian conformal prediction. The proposed system includes three components: OCR reading, text classification and product verification. By using image data from existing grocery stores, the system can detect anomalies with high performance, even when there is partial text information on the products. This makes the system applicable for reducing shrinkage loss (caused, for example, by employee theft or shoplifting) in grocery stores by identifying fraudulent behaviours such as barcode switching and miss-scan. Additionally, OCR reading with NLP classification shows that it is in itself a powerful classifier of products. 

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 188, article id 115942
Keywords [en]
Mondrian conformal prediction, OCR classification, Retail product verification, Smart self-checkout system, Classification (of information), Forecasting, Text processing, Business models, Conformal predictions, Digital transformation, Grocery stores, Mondrian, Product verification, Sales
National Category
Computer Sciences
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-20675DOI: 10.1016/j.eswa.2021.115942ISI: 000768193500002Scopus ID: 2-s2.0-85117127725OAI: oai:DiVA.org:his-20675DiVA, id: diva2:1606938
Note

CC BY-NC-ND 4.0

© 2021 The Authors

Corresponding author: rachid.oucheikh@ju.se (R. Oucheikh)

Corresponding author at ITAB Shop Products AB, Sweden: tobias.pettersson@itab.com (T. Pettersson)

tuwe.lofstrom@ju.se (T. Löfström)

URL: https://ju.se/jail/datakind (R. Oucheikh)

Available from: 2021-10-29 Created: 2021-10-29 Last updated: 2022-04-11Bibliographically approved

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Pettersson, Tobias

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