Text Extraction from Blurred Images through NLP-based Post-processing

Text extraction from blurred images is a difficult task in the field of computer vision. Traditional image processing methods often fail to accurately extract text from images with low resolution or high levels of noise. In the last few years, NLP techniques have been applied to improve the accuracy of text extraction from blurred images. This book chapter explores the use of NLP-based post-processing techniques to improve the quality of text extraction from blurred images. The chapter first provides an overview of traditional text extraction methods and the challenges associated with extracting text from blurred images. It then discusses the use of NLP techniques for improving the accuracy of text extraction. The chapter also explores the use of machine learning algorithms, such as convolutional neural networks, to enhance the performance of NLP-based post-processing techniques. Finally, the chapter provides a case study demonstrating the effectiveness of NLP-based post-processing techniques in improving text extraction from blurred images.