Novel receipt recognition with deep learning algorithms

Dong Xie; Colleen P. Bailey

doi:10.1117/12.2558206

22 April 2020 Novel receipt recognition with deep learning algorithms

Dong Xie, Colleen P. Bailey

Proceedings Volume 11400, Pattern Recognition and Tracking XXXI; 114000B (2020) https://doi.org/10.1117/12.2558206
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

We propose a new recognition method to extract effective information from receipts by integrating deep learning algorithms from computer vision and natural language processing. Our method consists of three parts. The first part provides effective areas for receipt detection. By removing noise and extracting the gradient of the receipt image, we determine the threshold to crop and reshape the useful receipt area. Detecting text from a receipt image is the second part, we modify and deploy the text detection algorithm connectionist text proposal network (CTPN) to locate the text region in the receipt. In the third part, we import the connectionist temporal classification with maximum entropy regularization as the loss function for updating the convolutional recurrent neural networks (CRNN) to recognize the text detection area, which converts the receipt from an image into the text. Based on our method, the effective information of a receipt can be integrated and utilized. We train and test our system using the data set published by scanned receipts optical character recognition and information extraction (SROIE). The results illustrate that our recognition system is able to identify receipt information quickly and accurately.

Conference Presentation

Citation Download Citation

Dong Xie and Colleen P. Bailey "Novel receipt recognition with deep learning algorithms", Proc. SPIE 11400, Pattern Recognition and Tracking XXXI, 114000B (22 April 2020); https://doi.org/10.1117/12.2558206

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