Procesado de documentos de texto mediante cGAN
Lahoz Torres, Aleix · UPCommons institutional repository (Universitat Politècnica de Catalunya) · 2021
In recent years, the introduction of Machine Learning together with the use of conventional image processing techniques has given a boost to automated document processing. One of the main issues that has compromised the performance of these automated systems has been the degradation the documents may present. Some kinds of degradation, such as document artifacts (watermarks, strips, stains?) or scan distortions can be difficult to remove with conventional methods, resulting in the deterioration of OCR systems. This study attempts to provide an end-to-end framework based on conditional GANs (cGANs) that restore degraded document images. Specifically, it intends to improve the text quality in documents to enhance the performance of subsequent automation systems. The outcome has been very satisfactory as the framework has been able to significantly increase the automation rate of the projects it has been tested in.