Benchmarking of Document Image Analysis Tasks for Palm Leaf Manuscripts from Southeast Asia

Made Kesiman,Jean-Christophe Burie,Mira Suryani,Setiawan Hadi,Dona Valy,Erick Paulus,Jean-Marc Ogier,Sophea Chhun,Michel Verleysen

doi:10.3390/jimaging4020043

Abstract

This paper presents a comprehensive test of the principal tasks in document image analysis (DIA), starting with binarization, text line segmentation, and isolated character/glyph recognition, and continuing on to word recognition and transliteration for a new and challenging collection of palm leaf manuscripts from Southeast Asia. This research presents and is performed on a complete dataset collection of Southeast Asian palm leaf manuscripts. It contains three different scripts: Khmer script from Cambodia, and Balinese script and Sundanese script from Indonesia. The binarization task is evaluated on many methods up to the latest in some binarization competitions. The seam carving method is evaluated for the text line segmentation task, compared to a recently new text line segmentation method for palm leaf manuscripts. For the isolated character/glyph recognition task, the evaluation is reported from the handcrafted feature extraction method, the neural network with unsupervised learning feature, and the Convolutional Neural Network (CNN) based method. Finally, the Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) based method is used to analyze the word recognition and transliteration task for the palm leaf manuscripts. The results from all experiments provide the latest findings and a quantitative benchmark for palm leaf manuscripts analysis for researchers in the DIA community.

Highlights

Since the world entered the digital age in the early 20th century, the need for a document image analysis (DIA) system is increasing
Besides aiming to preserve the existence of such ancient documents physically, the DIA system is expected to enable open access to the contents of the documents and provide opportunities for a wider audience to access all the important information stored in the document
DIA is the process of using various technologies to extract text, printed or handwritten, and graphics from digitized document files

Summary

Introduction

Since the world entered the digital age in the early 20th century, the need for a document image analysis (DIA) system is increasing. This is due to the dramatic increase in efforts to digitize the various types of document collections available, especially the ancient documents of historical relics found in various parts of the world. To accelerate the process of accessing, preserving, and disseminating the contents of the heritage documents, a DIA system is needed. DIA is the process of using various technologies to extract text, printed or handwritten, and graphics from digitized document files

Methods

Results

Conclusion