MC-OCR Challenge 2021: An end-to-end recognition framework for Vietnamese Receipts

Hung Le, H. To, Hung An, Khanh Ho, K. Nguyen, Thua Nguyen, Tien Do, T. Ngo, Duy-Dinh Le
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引用次数: 2

Abstract

Recognizing text from receipts is a significant step in automating office processes for many fields such as finance and accounting. MC-OCR Challenge has formed this problem into two tasks (1) evaluating the quality, and (2) recognizing required fields of the captured receipt. Our proposed framework is based on three key components: preprocessing with receipt detection using Faster R-CNN, alignment based on the angle and direction of rotation; estimate the receipt image quality score in task 1 using EfficientNet-B4 which has been retrained using transfer learning; while PAN is for text detection and VietOCR1 for text recognition. In the final round, our systems have achieved the best result in task 1 (0.1 RMSE) and a comparable result with other teams (0.3 CER) in task 2 which demonstrated the effectiveness of the proposed method.
MC-OCR挑战2021:越南收据的端到端识别框架
从收据中识别文本是许多领域自动化办公流程的重要一步,例如财务和会计。MC-OCR Challenge将该问题分为两个任务(1)评估质量,(2)识别捕获收据的必要字段。我们提出的框架基于三个关键组件:使用Faster R-CNN进行接收检测的预处理,基于旋转角度和方向的对齐;在任务1中,使用经过迁移学习再训练的EfficientNet-B4估计接收图像质量分数;而PAN用于文本检测,VietOCR1用于文本识别。在最后一轮中,我们的系统在任务1中取得了最好的结果(0.1 RMSE),并在任务2中与其他团队取得了相当的结果(0.3 CER),这证明了所提出方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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