Palm Leaf Manuscripts Research Articles

Study on the Effects of Temperature and Relative Humidity on the Hygroscopic Properties of Palm Leaf Manuscripts

Study on the Effects of Temperature and Relative Humidity on the Hygroscopic Properties of Palm Leaf Manuscripts

An intelligent character segmentation system coupled with deep learning based recognition for the digitization of ancient Tamil palm leaf manuscripts

Palm-leaf manuscripts, rich with ancient knowledge in areas such as history, art, and medicine, are vital cultural treasures, making their digitization essential for preserving this heritage. Digitization of these organic and fragile manuscripts is required to safeguard the essential ancient data. This requires optimal character segmentation and recognition algorithms. A limited number of studies have been carried out in Tamil character recognition in literature. Handling row-overlapped characters, noise introduced due to lightning issues, and dirt, as well as the removal of punch holes, auto-cropping the content, filtering out noisy or improper segmentation, etc. are the essential concerns carried out in our proposed work. This work is executed as a four-step process (1) Palm Leaf Manuscript Acquisition (2) Pre-Processing (3) Segmentation of Tamil Characters and (4) Tamil Character Recognition. During acquisition, the scanners are used for recording palm leaf manuscripts from the Tamil Nadu-oriented manuscript library. In the Pre-processing step, the Fast Non-Local Means (Fast-NLM) method, paired with median filtering is used for Denoising the scanner output image. Later, the pixels that make the characters and borders (i.e., the foreground) are identified using Sauvola thresholding. The proposed methodology introduces efficient techniques to remove Punch hole impressions from the pre-processed image, and to crop the written content from the edges. After pre-processing, the Segmentation of Tamil Characters is performed as a three-step process (a) Manuscript (b) Line, and (c) character segmentation, which addresses conjoined lines, partially/completely empty segmentations that are not previously addressed by existing techniques. This work introduces an Augmented HPP line-splitting algorithm that accurately segments written lines, handling wrong segmentation cases that were previously not considered by existing techniques. The system achieves an average segmentation accuracy of 98.25%, which far outperforms existing techniques. It also proposes a novel Punch hole removal algorithm that can locate and remove the punch-hole impressions in the manuscript image. This algorithm, along with the automated content cropping technique, increases recognition accuracy and eliminates any manual labor needed. These features make the proposed methodology highly suitable for real-time archaeological and historical researches that include manuscripts. All 247 letters and 12 numeric digits are analyzed and separated into 125 distinct writable characters. In our work, characters are segmented and used for recognition of all 247 letters and 12 digits in Tamil using a multi-class CNN with 125 classes, which drastically reduces the complexity of the neural network compared to having 257 output nodes. It offered a notable performance of 96.04% accuracy. As compared with existing Tamil and other character recognitions, this work is effective in essence of considering real-time images and the increased number of characters used.

Clay sealings from Perlis, Malaysia, and the wider world of the Bodhigarbhālaṅkāralakṣa-Dhāraṇī

Abstract Multiple copies of a particular clay sealing bearing the Buddhist Bodhigarbhālaṅkāralakṣa-dhāraṇī (mantra) inscription were discovered in Gua Berhala—a cave in Perlis, Malaysia. These sealings can be roughly assigned to the tenth century and they appear to have been stamped with an identical seal. However, critical reading of the textual rendition of the dhāraṇī had not yet been done despite several attempts to study it. Therefore, based on several fragments of these sealings, this article provides a detailed reading and translation of the dhāraṇī and considers the cultural significance of their production. The article also examines the textual structure of this Perlis dhāraṇī and compares it with similar dhāraṇīs preserved in a palm-leaf manuscript and other materials found across Asia. This includes a survey on the wider transmission of the dhāraṇī in the continent. In this comparative exercise, the physical characteristics of the Perlis sealing appear to be unique and express a distinct artistic style, while its textual tradition is slightly compressed compared with others, with no identical equivalent found elsewhere. This observation suggests that Perlis, with its proximity to the Bujang Valley, participated in the wider network of dhāraṇī culture rooted in Eastern India and was just not a passive recipient of this practice.

Material Characterisation of 19–20th Century Manuscripts from Northern Thailand

Abstract Material analysis was carried out on four manuscripts from Northern Thailand, which included two palm-leaf manuscripts and two paper manuscripts. The two palm-leaf manuscripts MS 6 and MS 7 were found to have been written in the traditional method, wherein text was incised on the surface of the leaves, and then soot applied to the surfaces, confirmed by the identification of carbon ink. MS 7 additionally showed the presence of trace levels of iron in the ink, either from soot paste or from the stylus used for inscribing. The paper manuscript MS 3 was written in iron-gall ink, with sections written using a methyl-violet based ink while MS 4 was written in carbon ink. The paper used in the case of MS 3 was found to be machine made, while khoi fibres (Streblus asper) were used for making the paper used for MS 4. A combination of traditional and modern pigments, like molybdenum orange, was used for decorating the edges and cover. The results improved our understanding of these manuscripts in particular, and also provided us with insights about the rapid adoption of modern materials and their incorporation into the production of written artefacts from Northern Thailand in the late 19th and early 20th centuries.

The effect of traditional processing craft on the hygroscopicity of palm leaf manuscripts

Palm leaf manuscripts, which are crucial carriers of historical, religious, scientific, and artistic information in East and Southeast Asia, specifically encapsulate significant aspects of Buddhist culture and thus require comprehensive research and preservation efforts. The base material of palm leaf manuscripts is processed palm leaves, which are hygroscopic and profoundly affected by environmental humidity. Currently, there is a research gap regarding the impact of traditional processing crafts and natural aging on the hygroscopicity of palm leaf manuscripts. Utilizing dynamic water vapor sorption (DVS), the hygroscopic properties of palm leaves from various years were assessed before and after traditional processing in Yunnan Province, China. The results show that traditional processing slightly increases the equilibrium moisture content (EMC) in environments with 0 to 60% relative humidity (RH), but significantly lowers EMC in high humidity environments, with reductions up to 19.01%. Additionally, hysteresis doubled post-processing, indicating enhanced stability under fluctuating humidity conditions. Sorption models suggest that traditional processing increases the number of adsorption sites while reducing physical adsorption or capillary condensation. FT-IR (Fourier-transform infrared spectroscopy) analysis indicates that the relative contents of cellulose and hemicellulose were reduced by 39.90% and 3.97%, respectively. Degradation occurring in both the crystalline and amorphous regions of cellulose. After natural aging, the hygroscopicity of processed palm leaves improved across the entire humidity range of 0 to 95%, and there was a slight increase in hysteresis. This is due to the increase in both adsorption sites and physical adsorption capabilities. FT-IR results also indicate that the relative contents of cellulose and hemicellulose were decreased by 57.52% and 19.83% after nature aging, respectively. These findings confirm that traditional processing improves the writability and humidity resilience of the leaves, while natural aging enhances their overall hygroscopic properties. This research contributes to our understanding of how humidity damages palm leaf manuscripts. aids in determining optimal RH ranges for storage, and assesses the effectiveness of consolidation treatments in their long–term preservation.

PLM-Res-U-Net: A light weight binarization model for enhancement of multi-textured palm leaf manuscript images

This paper proposes a deep semantic binarization model, PLM-Res-U-Net, for enhancing palm-leaf manuscripts. PLM-Res-U-Net is a lightweight model comprising encoding and decoding blocks with skip connections. The model enhances the palm leaf manuscript by efficiently retaining the text strokes by removing the degradations such as uneven illumination, aging marks, brittleness, and background discolorations. Two datasets of palm leaf manuscript collections with multiple degradation patterns and diverse textured backgrounds are used for experimentation. PLM-Res-U-Net is trained from scratch with 50 epochs with a learning rate of1e−8 with three sampling strategies. The performance of state-of-the-art deep learning models ResUnet, Pspnet, U-Net++, and Segnet are also evaluated along with two diverse benchmark datasets. Analysis shows that results obtained by the proposed PLM-Res-U-Net prove generalizability and computational efficacy with a dice score of 0.986. Additionally, PLM-Res-U-Net successfully preserves the edge strokes of the text compared with state-of-the-art models.

Analysis of Aspergillus niger isolated from ancient palm leaf manuscripts and its deterioration mechanisms

Palm leaf manuscripts (PLMs), venerable historical artefacts containing Buddhist scriptures, history, mathematics and literature, which are carried by palm leaves (Corypha umbraculifera) and are highly susceptible to microbial degradation during prolonged storage. This degradation results in significant alterations to both the appearance and material properties of PLMs, but the precise mechanism underlying this deterioration remains a mystery. To this end, the present study focused on ancient PLMs from Xishuangbanna Dai Autonomous Prefecture in Yunnan Province, China. The objective of present study was to isolate, culture and identify the microorganisms typically found in these manuscripts and to use them to biodegrade the carriers of PLMs. Detailed observations of the biodegradation behavior of these microorganisms on the carriers of PLMs were carried out, together with characterizations of the hierarchical structure and mechanical properties of the leaf fiber cell walls. This comprehensive analysis provided insights into the deterioration mechanisms of the carriers of PLMs. The study revealed the presence of the common fungus Aspergillus niger on ancient PLMs. Aspergillus niger can secrete cellulase, lipase, and acidic substances after colonizing on the carriers of PLMs. These substances sequentially damage the carrier's epidermal cells, mesophyll cells, and leaf fibers, leading to the separation of different tissue structures. At the molecular level, the lipids on the surface of the leaves were degraded initially, and sequential depolymerization of hemicellulose, amorphous cellulose, and crystalline cellulose occurred. Additionally, this study firstly applied nanoindentation technology in the research of PLMs. The mechanical properties of the cell walls underwent notable alterations due to the modifications in chemical and crystalline structure of the carriers of PLMs upon the biodegradation of Aspergillus niger. Specifically, the hardness and elastic modulus of leaf fiber cell walls showed an initial increasing and then decreasing trend, consistent with the trend of cellulose crystallinity, which also provided a new reference for assessing the degree of deterioration of PLMs.

Generate, transform, and clean: the role of GANs and transformers in palm leaf manuscript generation and enhancement

Generate, transform, and clean: the role of GANs and transformers in palm leaf manuscript generation and enhancement

V. M. Kuṭṭikṛṣṇa Mēnōn: An unmatched scholar of traditional Ayurveda system of medicine

Abstract V. M. Kuṭṭikṛṣṇa Mēnōn was an eminent Ayurveda physician, an astute researcher, and an insightful and eloquent writer. He is the author of three great books on Ayurveda and myriad publications on Ayurveda and folklore. The translation of Vāgbhaṭa’s Aṣṭāṅgahṛdayam (Sūtrasthāna), the quintessence and their treatment, and the publication of “Kriyākaumudi” and “Cikitsākautukam,” can all be seen as efforts to revive Kerala’s ancient traditions. As his writings were available only in the native Malayalam language, he remained unknown to other parts of the country. He perused innumerable palm leaf manuscripts from private collections and manuscript repositories at Thiruvananthapuram and Kozhikode, the contents of which otherwise would have never appeared in publications. He has not received much recognition and rewards that he deserved, but his insatiable thirst for knowledge has urged him to dig deep into the treasures of Ayurveda.

The Chinese Pothi: A Missing Link in the History of the Chinese Book

This paper examines Chinese pothi manuscripts from Dunhuang, arguing that this book form played an important role in the history of the Chinese book. Ultimately emulating Indian palm leaf manuscripts, the few dozen examples of Chinese pothi come from Dunhuang, where they appeared during the Tibetan control of the region. Rather than being a local phenomenon, the pothi form was instrumental in the development of more mainstream book forms, most notably the concertina.

A Study on Punya Lekhana Tradition in Sri Lanka: with reference to Kandyan Era

From the ruler to the ordinary citizens, the documents that record the meritorious deeds can be called 'Punya Lekhana'. The history of writing these documents can be traced back to time immemorial. The primary influence of these writings was the belief in meritorious acts of man, and the ideas and ideologies on good deeds and as shaped up by tradition. The aim of this research was to study the charity writing tradition in Sri Lanka and the research question was whether this tradition continued during the Kandyan Period. Historical methodology was applied for this research. It seems that the idea of keeping a record of the merits done by oneself started at the beginning of the Kandyan era, and 'Punya Lekhana' was compiled to record the merits done by the king and the ordinary people. It was a custom to prepare and keep the most common pious writings written in a temple using palm leaf medium as an appendix to a palm leaf manuscript or as a palm leaf manuscript. Since there are charitable documents of various natures, classification is possible according to their nature. These are Punyanumodhana Patra, Pundyanumodhana Sandesa, Punya Pustaka and Punya Ayadeum Patra. It is evident that these charity writings can be useful to genealogists to obtain information on genealogy. However it can be said that these documents were not been used as primary sources in historical research. This study underlines the fact that these are a unique source of literature in studying the religious, political and socio-economic history of the kandian Period.

Revealing the Mechanism of Ink Flaking from Surfaces of Palm Leaves (Corypha umbraculifera).

Palm leaves are the primary literary support in South and Southeast Asia before the widespread use of paper. However, palm leaf manuscripts face the threat of information loss due to the persistent issue of ink flaking during long-term preservation. Herein, we focus on studying the botanical structure, surface properties, and surface composition of palm leaves to gain an insightful understanding of the mechanism of ink flaking. According to the surface energy analysis, the surface of palm leaves is dominated by the dispersive component due to the presence of hydrophobic substances, resulting in the weak interaction between the handwriting and palm leaves. Moreover, the accumulation of silicon on palm leaves creates a "cuticle-silicon double layer", leading to a dense structure that hinders deep ink absorption. These two main reasons are considered to cause the ink flaking easily, which is further proven by the ink flaking test with the simulated palm leaf manuscripts. To the best of our knowledge, this is the first in-depth technical study on the adhesion performance of handwriting on plant leaves. This work also provides a theoretical basis for the study of the deterioration, adhesive repair, enhancement of flexibility, handwriting reinforcement, and beyond, which contributes to the conservation of precious palm leaf manuscripts.

A modified deep semantic binarization network for degradation removal in palm leaf manuscripts

A modified deep semantic binarization network for degradation removal in palm leaf manuscripts

A systematically evolved method for the effective use of essential oil blends for the structural maintenance of palm leaf manuscripts

Palm leaf manuscripts (PLMs) are traditional carriers that contain a wealth of knowledge from different disciplines written by ancient scholars. However, PLMs are susceptible to deterioration due to moisture, light, fungi and bacteria. An existing method of applying essential oils (EOs) to preserve PLMs does not currently appear successful, hence the study presented here which aimed to maximise the preservation characteristics of six different EO blends, prepared and applied to palm leaves, which were then tested for stiffness, brightness and weight gain. The interpretation of the efficiency of EO blends in the preservation of PLMs is attributed to the compatibility between the oils due to the various constituents present in the individual EOs. FTIR spectroscopy was used to understand the compatibility of the oils in a blend and any EO blend rendering a higher stiffness and brightness was identified as having a high preservation performance. Based on the investigation, good compatibility is observed between the FTIR spectrum of Blend-E with its contributing EOs of citronella, neem and mustard. On the other hand, Blend-B exhibits poor preservation characteristics and incompatibility. The study concludes with the recommendation that Blend-E is suitable for the treatment and regular maintenance of PLMs as it can help reduce physical and chemical damage.

Automatic damage identification of Sanskrit palm leaf manuscripts with SegFormer

AbstractPalm leaf manuscripts (PLMs) are of great importance in recording Buddhist Scriptures, medicine, history, philosophy, etc. Some damages occur during the use, spread, and preservation procedure. The comprehensive investigation of Sanskrit PLMs is a prerequisite for further conservation and restoration. However, current damage identification and investigation are carried out manually. They require strong professional skills and are extraordinarily time-consuming. In this study, PLM-SegFormer is developed to provide an automated damage segmentation for Sanskrit PLMs based on the SegFormer architecture. Firstly, a digital image dataset of Sanskrit PLMs (the PLM dataset) was obtained from the Potala Palace in Tibet. Then, the hyperparameters for pre-processing, model training, prediction, and post-processing phases were fully optimized to make the SegFormer model more suitable for the PLM damage segmentation task. The optimized segmentation model reaches 70.1% mHit and 51.2% mIoU. The proposed framework automates the damage segmentation of 10,064 folios of PLMs within 12 h. The PLM-SegFormer framework will facilitate the preservation state survey and record of the Palm-leaf manuscript and be of great value to the subsequent preservation and restoration. The source code is available at https://github.com/Ryan21wy/PLM_SegFormer.

Analysis of Two Different Inks and Application Techniques on Palm Leaf Manuscripts Through Non-Invasive Analysis

Abstract Influenced by the spreading route of Buddhism, palm leaf manuscripts in China are mostly distributed in Yunnan province and Tibet. The ink of palm leaf manuscripts from Yunnan province is left in the incisions, while the ink of palm leaf manuscripts from Tibet is written on the surface. The two inks have different compositions and application techniques, which may lead to varying degrees of flaking and ink loss. Application technique and ink composition are crucial for conservation measures. In this study, non-destructive analysis techniques including a portable digital microscope, Fourier transform infrared spectroscopy (FTIR), and X-ray fluorescence (XRF) were undertaken to analyse the characteristics and preservation condition of inks applied with different techniques on palm leaf manuscripts. Morphologies indicated that the interaction of ink and support influence the type and extent of ink loss. FTIR and XRF results showed significant differences in ink composition between incised palm leaf manuscripts from Yunnan and surface-written manuscripts from Tibet. Manuscripts from different periods within the same region exhibited similarities in ink composition. This paper significantly contributes to understanding properties of inks, offering an essential reference for ink consolidation.

Evaluation of the Deterioration State of Historical Palm Leaf Manuscripts from Burma

Palm leaf manuscripts were a prevalent literary medium from South Asia and Southeast Asia prior to the widespread use of paper. This study focuses on the analysis of historical palm leaf manuscripts from South and Southeast Asia. Sample palm leaf manuscripts from Burma were used as a case study; simulated palm leaf manuscripts were also created as a reference for comparison. The anatomy, chemical composition, and mechanical properties of the manuscripts were analyzed to find various forms of deterioration, including damage, fractures, pollution, acidification, and microbial deterioration. Specifically, the S1–S3 layers of the cell walls exhibited complete cracking, and the S2 layer showed numerous circular or nearly circular cavities caused by microbial erosion, while the middle lamella remained intact. The severe degradation of polysaccharides and pectin, accompanied by an increase in the relative content of lignin, caused the historical manuscripts to become more brittle. Additionally, the tensile strengths of historical palm leaf manuscripts were markedly reduced; their longitudinal tensile strength was significantly greater than their transverse tensile strength. This study can contribute to a better understanding of the deterioration process of historical palm leaf manuscripts and provide valuable insights for their restoration and preservation.

ENSEMBLING DEEP CONVOLUTIONAL NEURAL NEWORKS FOR BALINESE HANDWRITTEN CHARACTER RECOGNITION

While deep learning has proven its performance in various problems and applications, it also opens opportunities in a new way to promote the heterogeneity of cultures and heritages. Balinese script is a cultural heritage in Bali, where it is used to write on palm-leaf manuscripts and contains essential information. Most manuscripts were damaged due to age and lack of maintenance, so a digitalization technique should be developed. In this study, we propose an ensemble of deep convolutional neural networks to recognize the handwritten characters in the Balinese script. We extensively compared various deep convolutional neural network architectures, and the results showed that our ensemble methods achieved the state of the art.

Deteriorated image classification model for malayalam palm leaf manuscripts

The method for document image classification presented in this paper mainly focuses on six different Malayalam palm leaf manuscripts categories. The proposed approach consists of three phases: dataset analysis, building a bag of words repository followed by recognition and classification using a voting approach. The palm leaf manuscripts are initially subject to pre-processing and subjective analysis techniques to create a bag of words repository during the dataset analysis phase. Next, the textual components from the manuscripts are extracted for recognition using Tesseract 4 OCR with default and self-adapted training sets and a deep-learning algorithm. The Bag of Words approach is used in the third phase to categorize the palm leaf manuscripts based on textual components recognized by OCR using a voting process. Experimental analysis was done to analyze the proposed approach with and without the voting techniques, varying the size of the Bag of Words with default/self-adapted training datasets using Tesseract OCR and a deep learning model. Experimental analysis proves that the proposed approach works equally well with/ without voting with a bag of words technique using Tesseract OCR. It is noticed that, for document classification, an overall accuracy of 83% without voting and 84.5% with voting is achieved with an F-score of 0.90 in both cases using Teserract OCR. Overall, the proposed approach proves to be high generalizable based on trial wise experiments with Bag of Words, offering a reliable way for classifying deteriorated Malayalam handwritten palm manuscripts.

Text line extraction strategy for palm leaf manuscripts

Text line segmentation is an important step in the historical document image analysis pipeline to supply useful information for recognition, keyword spotting and indexing. Many handcrafted-based and learning-based approaches have been developed to cope with text line extraction challenges. In this work we present a hybrid technique which combines a convolutional-based denoising task and heuristic Seam Carving framework. We propose the following changes to the original Seam Carving: (1) We applied adaptive slice to anticipate miss-extraction on a short text during medial seam computation. (2) We applied a triple smoothing to find the best local maxima of the smoothed horizontal projection profile which represents candidate medial seams. (3) We utilized five post-processing steps aimed at reconstructing a more precise medial seam. Three different palm leaf data sets: old Sundanese, old Balinese, and old Khmer, have been used to compare Convolutional Seam Carving (CSC) to several baseline methods, including the original Seam Carving. Experimental results show that the proposed method outperforms other current handcrafted-based baselines on all three palm leaf manuscript (PLM) data sets. On the old Sundanese data sets, CSC can produce a significant improvement of the performance rate compared to all other baseline approaches, and it also enhance the measurement on old Balinese and old Khmer datasets. In the ablation study, we discovered that a foreground extraction step is not only able to reduce noises and color degradation but also provide better separation of text region. Following that, an adaptive slice and triple smoothing approach contribute to solve the text length variation problem. Finally, post-processing steps were effective in connecting discontinuous medial seam. The code has been published in https://github.com/erickpaulus/text-line-segmentation.