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基于表格识别的餐饮业进出货台账图片识别方法

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针对当前表格识别算法对于餐饮业进出货台账图片在自然场景情况下文本和表格识别能力弱的问题,在参考以往表格识别算法架构基础上,提出了一种基于改进的DBNet文本检测算法、SPIN场景文本识别算法与TableMaster表格识别算法的台账图片表格识别算法.改进的DBNet文本检测算法在DBNet算法的特征提取网络中引入了自适应尺度融合模块ASF,有效提升了文本定位能力;采用SPIN场景文本识别算法代替CRNN识别算法,增强了其对自然场景中倾斜、模糊、扭曲文本的识别能力;采用TableMaster识别算法代替PLANet表格识别算法,增强了在轻量化条件下的识别能力和准确度.将文本检测与表格识别模型联合串联推理,在测试场景下达到了 94.7%的识别率,具有较高的实用价值.
Image Recognition Method of Import and Export Ledger of Catering Industry Based on Table Recognition
Aiming at the problem that the current table recognition algorithm has weak text and table recognition ability for the food and beverage import and shipment account pictures in natural scenes,this paper refers to the previous table recognition algorithm architecture.This paper presents an algorithm for table recognition of ledger picture based on im-proved DBNet text detection algorithm,SPIN scene text recognition algorithm and TableMaster table recognition algorithm.The TableMaster recognition algorithm is used instead of the PLANet table recognition algorithm,which enhances the recog-nition capability and accuracy under lightweight conditions.In this paper,text detection and form recognition model are combined with series inference,and the recognition rate is 94.7%in test scenarios,which has high practical value.

table identificationDBNetSPINTableMasterledgercatering industry

汪浩

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上海大学通信与信息工程学院,上海 200444

表格识别 DBNet SPIN TableMaster 台账 餐饮业

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(10)