Dr. Ravi Kiran Sarvadevabhatla and his students Niharika Vadlamudi  and   Rahul Krishna   presented a paper on SeamFormer: High Precision Text Line Segmentation for Handwritten Documents at the 17th International Conference on Document Analysis and Recognition (ICDAR 2023) held at San Jose, USA from 21 to 26 August.

Here is the summary of the paper as explained by the authors:

Historical manuscripts often contain dense unstructured text lines. The large diversity in sizes, scripts and appearance makes precise text line segmentation extremely challenging. Existing line segmentation approaches often associate diacritic elements incorrectly to text lines and also address above mentioned challenges inadequately. To tackle these issues, we introduce SeamFormer, a novel approach for high precision text line segmentation in handwritten manuscripts. In the first stage of our approach, a multi-task Transformer deep network outputs coarse line identifiers which we term ‘scribbles’ and the binarized manuscript image. In the second stage, a scribble-conditioned seam generation procedure utilizes outputs from the first stage and feature maps derived from manuscript image to generate tight-fitting line segmentation polygons. In the process, we incorporate a novel diacritic feature map which enables improved diacritic and text line associations. Via experiments and evaluations on new and existing challenging palm leaf manuscript datasets, we show that SeamFormer outperforms competing approaches and generates precise text line segmentations.KeywordsText Line SegmentationHistorical Manuscripts

Know more about the research work: https://ihdia.iiit.ac.in/seamformer/ 

Conference page: https://icdar2023.org/

September 2023