多个OCR表检测和提取的集合
A Conglomerate of Multiple OCR Table Detection and Extraction
摘要：
用表格表示信息是一种紧凑而简洁的方法，可以简化搜索、索引和存储要求。从可解析文档中提取和克隆表更容易且应用广泛，但行业在从OCR文档或图像中检测和提取表方面仍面临挑战。本文提出了一种从OCR文档中检测和提取多表的算法。该算法使用图像处理技术、文本识别和程序编码的组合来识别同一图像中的不同表格，并将文本映射到可存储为逗号分隔值、数据库、Excel和多种其他可用格式的点阵中的适当的对应单元格。
英文摘要：
Information representation as tables are compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used, however industry still faces challenge in detecting and extracting tables from OCR documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition and procedural coding to identify distinct tables in same image and map the text to appropriate corresponding cell in dataframe which can be stored as Comma-separated values, Database, Excel and multiple other usable formats.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
