Comprehensive Analysis and Framework for Text and Graphics Separation in Document Images

The process of breaking up a digital image into many parts is called segmentation. These sections in scanned papers, are those that have backgrounds, texts, and images. In applications linked to document analysis, text segmentation is a significant issue. The separation of a complex document into non-text and text components is a major challenge in document image analysis. Localization of text in printed document images is a critical processing step for page layout analysis (PLA), specifically for obtaining textual data. Several algorithms have been developed for this subject. However, many algorithms only produce accurate answers for a limited type of documents due to their reliance on specific attributes or assumptions. There is a need to develop effective techniques for many sorts of documents, such as newspapers, magazines, documents, and articles, with arbitrary layouts and nonhomogeneous backgrounds. This study examines the various ways that distinguish between non-text and text in document images.