HInDoLA: A Unified Cloud-Based Platform for Annotation, Visualization and Machine Learning-Based Layout Analysis of Historical Manuscripts
Abhishek Trivedi, Ravi Kiran Sarvadevabhatla · 2019
Palm-leaf manuscripts are one of the oldest medium of inscription in many Asian countries. Especially, manuscripts from the Indian subcontinent form an important part of the world's literary and cultural heritage. Despite their significance, large-scale datasets for layout parsing and targeted annotation systems do not exist. Addressing this, we propose a web-based layout annotation and analytics system. Our system, called HInDoLA, features an intuitive annotation GUI, a graphical analytics dashboard and interfaces with machine-learning based intelligent modules on the backend. HInDoLA has successfully helped us create the first ever large-scale dataset for layout parsing of Indic palm-leaf manuscripts. These manuscripts, in turn, have been used to train and deploy deep-learning based modules for fully automatic and semi-automatic instance-level layout parsing.