Method for extracting and identifying graphic and text information of scanned document

Abstract

The invention relates to a method for extracting and identifying graphic and text information of a scanned document, which comprises the following steps of: 1) preprocessing a scanned document image,carrying out layout segmentation on the preprocessed image, and selecting items, including but not limited to, a signature and a seal; (2) preprocessing the signature extracted in the step (1), removing a background by adopting an OTSU algorithm, inputting the signature into a Writer-Dependent network to extract a characteristic value of the signature, and inputting the characteristic value into an SVM classifier obtained by using real signature training to obtain the authenticity of the signature; (3) conducting polar coordinate transformation on the seal extracted in the step (1) after preprocessing, so that annular characters in the seal are expanded into transversely-arranged characters, inputting the expanded characters into a CPTN + CRNN network to be sequentially extracted and recognized, and outputting the character content of the seal; 4) judging the validity of the document. The method can replace manual work to analyze and judge the document.

Description

technical field [0001] The invention relates to the technical field of image-text recognition, and more specifically, relates to a method for extracting and identifying image-text information of scanned documents. Background technique [0002] OCR (optical character recognition, optical character recognition) can use optical equipment to capture images and recognize text, extend the ability of the human eye to the machine, and recognize the graphic information in the scanned document into editable text, which can replace manual input , improve business efficiency. In actual work, document processors often use key content such as the date, signature and seal of the document to identify the category and validity of the document. At present, the extraction and identification of document information are all done manually, which is inefficient and has misjudgments and omissions. Therefore, it is of great significance in practical work to use OCR and image processing related tec...

AI Technical Summary

Problems solved by technology

[0005] Great progress has been made in the recognition of simple printed documents and text detection and recognition in complex scenes, but there is no effective method for the extraction and identification of key information in documents.

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