Comparing Binarisation Techniques for the Processing of Ancient Manuscripts

Chamchong, Rapeeporn; Fung, Chun Che; Wong, Kok Wai

doi:10.1007/978-3-642-15214-6_6

Cited by 14 publications

(8 citation statements)

References 16 publications

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“…The performance of binarization techniques has a great impact and directly affects the performance of the recognition task [35]. Non-optimal binarization methods produce unrecognizable characters with noise [16]. Many binarization methods have been reported.…”

Section: Binarizationmentioning

confidence: 99%

“…These methods have been tested and evaluated on different types of document collections. Based on the choice of the thresholding value, binarization methods can generally be divided into two types, global binarization and local adaptive binarization [16]. Some surveys and comparative studies of the performance of several binarization methods have been reported [35,36].…”

Section: Binarizationmentioning

confidence: 99%

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

et al. 2018

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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.

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Section: Binarizationmentioning

confidence: 99%

Section: Binarizationmentioning

confidence: 99%

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

et al. 2018

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“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Kesiman

Prum

Burie

et al. 2016

2016 23rd International Conference on Pattern Recognition (ICPR)

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The complexity of Balinese script and the poor quality of palm leaf manuscripts provide a new challenge for testing and evaluation of robustness of feature extraction methods for character recognition. With the aim of finding the combination of feature extraction methods for character recognition of Balinese script, we present, in this paper, our experimental study on feature extraction methods for character recognition on palm leaf manuscripts. We investigated and evaluated the performance of 10 feature extraction methods and we proposed the proper and robust combination of feature extraction methods to increase the recognition rate.

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“…In the last five years, ancient palm leaf manuscripts have received great attention from researchers in the field of document image analysis. For example, a digitization project for palm leaf manuscripts from Cambodia 1 and Thailand [1], [2].…”

Section: Introductionmentioning

confidence: 99%

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

Kesiman

Prum

Burie

et al. 2015

2015 13th International Conference on Document Analysis and Recognition (ICDAR)

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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.

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Comparing Binarisation Techniques for the Processing of Ancient Manuscripts

Cited by 14 publications

References 16 publications

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

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

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

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

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