Lecture automatique d'un ticket de caisse par vision embarquée sur un téléphone mobile

Travaux réalisés dans le cadre d'une thèse CIFRENational audienceThis work addresses the automatic reading of sale receipts acquired with a smartphone's camera and the extraction of essential informations like the store brands, all the purchased products , their price etc. It is divided into two major tasks : the optical character recognition that is made complex due to the nature of the document often damaged, crumpled or torned and the semantic data analysis to identify purchased product without ambiguity. In this paper, we introduce a solution that enables a "guided" capture on smartphone and a receipt decoding on remote server.L'objectif de ces travaux est de créer un système capable, à partir d'une simple vue prise par un smartphone, d'exploiter le contenu d'un ticket de caisse, et d'en extraire des informations telles que le point de vente, les produits ache-tés, leurs prix etc. On distingue deux étapes majeures : la reconnaissance optique de caractères sur des tickets qui peuvent être froissés, déchirés... et l'analyse sémantique afin d'identifier les produits achetés sans ambiguïté. Dans ce papier, nous présentons une solution qui effectue une acquisition "guidée" d'une image sur smartphone et une lecture du contenu sur un serveur distant

Deep Learning for automatic sale receipt understanding

International audienceAs a general rule, data analytics are now mandatory for companies. Scanned document analysis brings additional challenges introduced by paper damages and scanning quality.In an industrial context, this work focuses on the automatic understanding of sale receipts which enable access to essential and accurate consumption statistics. Given an image acquired with a smart-phone, the proposed work mainly focuses on the first steps of the full tool chain which aims at providing essential information such as the store brand, purchased products and related prices with the highest possible confidence. To get this high confidence level, even if scanning is not perfectly controlled, we propose a double check processing tool-chain using Deep Convolutional Neural Networks (DCNNs) on one hand and more classical image and text processings on another hand.The originality of this work relates in this double check processing and in the joint use of DCNNs for different applications and text analysis

TRAITEMENTS LINGUISTIQUES POUR LA RECHERCHE D'INFORMATION ET L'ANALYSE EN FOH DE REX FERROVIAIRES

International audienc