  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.
