Degraded Document Analysis

Degraded Document Analysis is a subfield of Document Image Analysis that specifically focuses on the development and application of methods, models, or frameworks to restore, enhance, and interpret historical, damaged, or low-quality document images characterized by imperfections such as noise, fading, bleed-through, or physical deterioration.

174

Publications

7.2K

Citations

382

Authors

165

Institutions

Publications per year

2017–2026

40

Authors

382

  1. MC
    Mohamed Cheriet

    École de Technologie Supérieure, Canada

    14 publications · 520 citations

    12

    h-index

  2. CL
    Chew Lim Tan

    National University of Singapore, Singapore

    7 publications · 438 citations

    7

    h-index

  3. SL
    Shijian Lu

    Nanyang Technological University, Singapore

    7 publications · 671 citations

    7

    h-index

  4. RF
    Reza Farrahi Moghaddam

    École de Technologie Supérieure, Canada

    7 publications · 399 citations

    7

    h-index

  5. AT
    Anna Tonazzini

    Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo", Italy

    6 publications · 332 citations

    6

    h-index

1–5 of 382

Venues

  1. 10

    h-index

  2. Pattern Recognition

    9 publications · 1.4K citations

    9

    h-index

  3. 5

    h-index

  4. 5

    h-index

  5. IEEE Transactions on Image Processing

    3 publications · 384 citations

    3

    h-index

1–5