A Method of Text Detection and Recognition from Receipt Images Based on CRAFT and CRNN. (April 2020)

• Record Type: Journal Article
• Authors: Wang, Xiaohui; Zhang, Xi; Lei, Shuya; Deng, Hongmei
• Is Part Of: Journal of physics. Volume 1518(2020)
• Publication Date: 2020-04
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1518/1/012053
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Text detection and recognition from paper bank receipts image has a lot of applications in the business field, such as in power system marketing, which is applied in verification and cancellation of electricity charges and automatic archiving. In this paper, we use a text detection method to effectively detect text area in receipt image by exploring each character and affinity between characters. Then put the text sequence into text recognizition model which is combined by DCNN and RNN and integrates feature extraction, sequence modeling and transcription. The experiments demonstrate the superiority of the proposed algorithm over the prior arts, which performs well in the task of blurred image-based bank receipt chinese text recognition.