An initial study on the construction of ground truth binarized images of ancient palm leaf manuscripts

Abstract

Ancient palm leaf manuscripts are one of the very valuable cultural heritages that store various forms of knowledge and historical records of social life in Southeast Asia. The automatic analysis of these documents, in order to extract relevant information, is a real challenge. However, to evaluate the developed extraction algorithms, a ground truth is absolutely necessary. In this paper, we present some of the challenges of the state of the art binarization methods as an initial study for the construction of ground truth binarized images of palm leaf manuscripts. We propose and analyze the need for a specific scheme for the construction of the ground truth of binarized images. The aim of this scheme is to achieve a better ground truth for low quality palm leaf manuscripts. We experimentally tested and evaluated our proposed specific scheme and got promising results. This scheme adapts and performs better in constructing the ground truth of binarized images for palm leaf manuscripts.

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

“…The Southeast Asian manuscripts with different scripts and languages provide real challenges for document analysis methods, not only because of the different forms of characters in the script, but also because the writing style of each script (e.g., how to join or separate a character in a text line) differs. It ranges widely from a binarization process [23][24][25], text line segmentation [26,27], and character and text recognition tasks [25,28,29], to the word spotting methods [30].…”

“…A pressure-sensitive tip stylus is used to trace each text stroke by keeping the original size of the stroke width [59]. For the manuscripts from Bali, the binarized ground truth images have been created with a semi-automatic scheme [17,[23][24][25] (Figure 12). The binarized ground truth images for Sundanese manuscripts were manually [22] generated using PixLabeler [60] (Figure 13).…”

“…We used all images of the Khmer and Sundanese corpuses as a test set because the training-based binarization method (ICFHR G1 method, see Section 5.1) was evaluated for the Khmer and Sundanese datasets by using only the pre-trained Balinese training set weighted model. images have been created with a semi-automatic scheme [17,[23][24][25] (Figure 12). The binarized ground truth images for Sundanese manuscripts were manually [22] generated using PixLabeler [60] ( Figure 13).…”

Study on feature extraction methods for character recognition of Balinese script on palm leaf manuscript images

“…In order to obtain the variety of the manuscript images, the sample images used in this experiment are randomly selected from 23 different collections (contents), with the total of 393 pages. By using the collection of wordlevel annotated patch images from our palm leaf manuscript collection, which were produced manually using Aletheia 3 [25] in our previous ground truthing process, we collected our isolated Balinese character dataset. We applied binarization process to automatically extract all connected component found on the word patch images.…”

“…For example, the IHCR challenges for historical documents discovered in the palm leaf manuscripts, written using the script originating from the region of Southeast Asia, such as Indonesia, Cambodia, and Thailand. Ancient palm leaf manuscripts from Southeast Asia have received great attention from historian and also researchers in the field of document image analysis, for example some works on document analysis of palm leaf manuscript from Thailand [1,2] and from Indonesia [3,4]. The physical condition of the palm leaf documents is usually degraded.…”