Analysis of Segmentation Methods for Brahmi Script

Singh, Ajay Pratap; Kushwaha, Ashwin Kumar

doi:10.14429/djlit.39.2.13615

Cited by 11 publications

(6 citation statements)

References 24 publications

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“…The process of this study was based on the concepts of text mining and NLP. For more, please refer to [5][6][7][14][15][16]18,[27][28][29][30]. In the SCI (science citation index) and SSCI (social science citation index) articles of [31], through the steps of text retrieval, word segmentation, word cloud analysis, TF-IDF analysis, co-word analysis, network analysis, trend analysis, etc., the text data of the two regions are excavated for comparison and analysis of their similarities and differences.…”

Section: Methodsmentioning

confidence: 99%

“…Words, phrases, and sentences are the basic units in the process of language recognition, and their meanings will affect the understanding of the text. Accurate word segmentation is very important [27,30]. In this study, the CKIP Chinese word segmentation system [17,28] was used to disassemble the words and mark the parts of speech of each vocabulary automatically.…”

Section: Word Segmentation and Word Cloud Analysismentioning

confidence: 99%

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Analysis of The Development Trend of Sports Research in China and Taiwan Using Natural Language Processing

Shih¹,

Ho²

2022

Preprint

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A digital text abstract presents the essential information of an article, and we can find the trend and value of the research by analyzing it rigorously and digging up knowledge. Therefore, this study focuses on the abstracts of index journals in China and Taiwan from July 2010 to June 2020 (a total of 3,283 abstracts). Through the concepts of text mining and natural language processing (NLP), it constructs processes such as text retrieval, text segmentation and word cloud analysis, TF-IDF weight analysis, co-word analysis, network analysis, and trend analysis, and analyses a large amount of text data. The results show that the scope of research in China covers the fields of social sports and sports science, and research in Taiwan covers both natural and social sciences. The network diagram highlights the richness of sports-related research fields in the two regions, but research on sports philosophy is relatively rare. It is suggested that all disci-plines/departments should re-allocate the same resources, so as to show a balanced development trend and help expand a new chapter in the sports academic field.

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Section: Methodsmentioning

confidence: 99%

Section: Word Segmentation and Word Cloud Analysismentioning

confidence: 99%

Analysis of The Development Trend of Sports Research in China and Taiwan Using Natural Language Processing

Shih¹,

Ho²

2022

Preprint

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“…Fig. 1 shows a sample Brahmi inscription from Ashoka Edict located at Sarnath [24] and Fig. 2 shows the characters of Brahmi script [25].…”

Section: Brahmi Script and Charactersmentioning

confidence: 99%

Efficient Scalable Template-Matching Technique for Ancient Brahmi Script營mage

Kaur¹,

Sagar²

2023

Computers, Materials &Amp; Continua

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Analysis and recognition of ancient scripts is a challenging task as these scripts are inscribed on pillars, stones, or leaves. Optical recognition systems can help in preserving, sharing, and accelerate the study of the ancient scripts, but lack of standard dataset for such scripts is a major constraint. Although many scholars and researchers have captured and uploaded inscription images on various websites, manual searching, downloading and extraction of these images is tedious and error prone. Web search queries return a vast number of irrelevant results, and manually extracting images for a specific script is not scalable. This paper proposes a novel multistage system to identify the specific set of script images from a large set of images downloaded from web sources. The proposed system combines the two most important pattern matching techniques-Scale Invariant Feature Transform (SIFT) and Template matching, in a sequential pipeline, and by using the key strengths of each technique, the system can discard irrelevant images while retaining a specific type of images.

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“…Apart from that, recently, few works also can see on Brahmi script such as Brahmi script to Pali language translation [10], Brahmi word segmentation [13]. All these studies completed on local Brahmi dataset.…”

Section: Literature Reviewmentioning

confidence: 99%

Brahmi Word Recognition by Supervised Techniques

Gautam¹,

Chai²,

Afrin³

et al. 2020

Preprint

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Significant progress has made in pattern recognition technology. However, one obstacle that has not yet overcome is the recognition of words in the Brahmi script, specifically the recognition of characters, compound characters, and word because of complex structure. For this kind of complex pattern recognition problem, it is always difficult to decide which feature extraction and classifier would be the best choice. Moreover, it is also true that different feature extraction and classifiers offer complementary information about the patterns to be classified. Therefore, combining feature extraction and classifiers, in an intelligent way, can be beneficial compared to using any single feature extraction. This study proposed the combination of HOG +zonal density with SVM to recognize the Brahmi words. Keeping these facts in mind, in this paper, information provided by structural and statistical based features are combined using SVM classifier for script recognition (word-level) purpose from the Brahmi words images. Brahmi word dataset contains 6,475 and 536 images of Brahmi words of 170 classes for the training and testing, respectively, and the database is made freely available. The word samples from the mentioned database are classified based on the confidence scores provided by support vector machine (SVM) classifier while HOG and zonal density use to extract the features of Brahmi words. Maximum accuracy suggested by system is 95.17% which is better than previously suggested studies.

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Analysis of Segmentation Methods for Brahmi Script

Cited by 11 publications

References 24 publications

Analysis of The Development Trend of Sports Research in China and Taiwan Using Natural Language Processing

Analysis of The Development Trend of Sports Research in China and Taiwan Using Natural Language Processing

Efficient Scalable Template-Matching Technique for Ancient Brahmi Script營mage

Brahmi Word Recognition by Supervised Techniques

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