BINYAS: a complex document layout analysis system

Document layout analysis (DLA) is an irreplaceable pre-requisite for the development of a comprehensive document image processing and analysis system. The main purpose of DLA is to segment an input document image into its constituent and coherent regions and identify their classes. In this paper, we propose a competent DLA system, named as BINYAS, based on the connected component (CC) and pixel analysis based approach. Here, we initially identify the regions and then classify these regions as paragraph, separator, graphic, image, table, chart, and inverted text etc. The proposed system is evaluated on four publicly available standard datasets, namely ICDAR 2009, 2015, 2017 and 2019 page segmentation competition datasets, and the performance is compared with many contemporary methods, which also include some well-known software products and deep learning based methods. Experimental results show that our method performs significantly better than state-of-the-art methods in terms of the evaluation metrics considered by the research community of this domain.

Automated summary

Document layout analysis (DLA) is essential for developing a comprehensive document image processing system, aiming to segment document images and identify different regions. The proposed BINYAS system, based on connected components and pixel analysis, outperforms existing methods based on evaluations on four standard datasets.