Survey of Post-OCR Processing Approaches | ACM Computing …
2021年7月13日 · This article clarifies the importance of enhancing quality of OCR results by studying their effects on information retrieval and natural language processing applications. We then define the post-OCR processing problem, illustrate its typical pipeline, and review the state-of-the-art post-OCR processing approaches.
Survey of Post-OCR Processing Approaches - ACM Digital Library
This article clarifies the importance of enhancing quality of OCR results by studying their effects on information retrieval and natural language processing applications. We then define the post-OCR processing problem, illustrate its typical pipeline, and review the state-of-the-art post-OCR processing approaches.
Optical character recognition with neural networks and post …
2020年8月20日 · There are many different approaches to OCR post-processing. Some of the basic methods look at post-correction as a sequence to sequence spelling correction task (e.g., [8, 24, 34]). In this work, we use a sequence to sequence method that can be described as an unstructured classifier and is proposed in . This is a relatively simple method from ...
Post-Processing OCR Text using Web-Scale Corpora
2017年8月31日 · Post-OCR is an important processing step that follows optical character recognition (OCR) and is meant to improve the quality of OCR documents by detecting and correcting residual errors. This paper describes the results of a statistical analysis of OCR ...
Statistical Post-processing Approaches for OCR Texts
2022年5月19日 · OCR post-processing can be applied as the last step of an OCR system or to the erroneous OCR texts. There are three possible ways to improve the quality of OCR texts: modifying input images, optimizing OCR system, and post-processing OCR texts.
OCR error correction using correction patterns and self …
2020年11月23日 · Post-processing is an essential step in improving the output quality of OCR systems by detecting and cleaning the errors. In this paper, we present an automatic model consisting of both error detection and error correction phases for OCR post-processing.
Deep Statistical Analysis of OCR Errors for Effective Post-OCR Processing
Post-OCR is an important processing step that follows optical character recognition (OCR) and is meant to improve the quality of OCR documents by detecting and correcting residual errors. This paper describes the results of a statistical analysis of OCR errors on four document collections.
Survey of Post-OCR Processing Approaches - Semantic Scholar
2021年7月1日 · This article clarifies the importance of enhancing quality of OCR results by studying their effects on information retrieval and natural language processing applications. We then define the post-OCR processing problem, illustrate its typical pipeline, and review the state-of-the-art post-OCR processing approaches.
Survey of Post-OCR Processing Approaches | Request PDF
2021年7月1日 · We then define the post-OCR processing problem, illustrate its typical pipeline, and review the state-of-the-art post-OCR processing approaches. Evaluation metrics, accessible datasets,...
Text Post-processing on Optical Character Recognition output …
This research work aims at addressing this shortcoming by performing post-processing on OCR outputs primarily using Transformers such as BERT in a two-step pipeline to correct these mistakes and improve the quality of the document.