2017/12/05 by Rizlène Raoui-Outach, Raoui-Outach, Rizlène, Cécile Million-Rousseau +6
Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Imbalanced Data Classification Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.1712.01606
International Conference on Image Processing Theory, Tools and Applications, Nov 2017, Montreal, Canada. 2017, http://www.ipta-conference.com/ipta17
arxiv created 2017/12/05 · openalex publication_date 2017/12/05 · arxiv updated 2017/12/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
As 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.