Jaimin Nitesh Shah
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In this project, we propose an Image Quality Assessment and Comparison metrics for Image denoising algorithms. It is well known that Image denoising plays a significant role in various Image related applications. Motivated by this, we attempt to develop Image quality assessment and comparison metrics specifically targeting image denoising algorithms. We have prepared a dataset containing images of text documents with appropriate noise specifically to meet the needs of this project. Images are denoised using different algorithms and then fed into an OCR engine to obtain text, we then compare it with text obtained using ground truth images which do not have any added noise to assess denoised image quality obtained using different algorithms Keywords—image denoising, image quality assessment (IQA), optical character recognition (OCR).
Van Tam Nguyen
Primary Advisor's Department
Stander Symposium project, College of Arts and Sciences
United Nations Sustainable Development Goals
Industry, Innovation, and Infrastructure; Quality Education
"Underwater Document Recognition" (2021). Stander Symposium Projects. 2144.
This poster reflects research conducted as part of a course project designed to give students experience in the research process. Course: CPS 599