Thai handwriting legal amounts recognition

Chatwiriya, Watchara; Klinkhachorn, P.; Lass, Norman J.

doi:10.1109/ssst.2003.1194596

Cited by 3 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Neural Network Based Approach. Neural Pattern Recognition emulates knowledge of how a biological neural system stores and manipulates information [15,16,17]. This artificial neural system is called "neural networks".…”

Section: Background Materialsmentioning

confidence: 99%

Lanna Handwritten Character Recognition on Historical Documents Using Feature Extraction

Khankasikam

2012

AMM

View full text Add to dashboard Cite

The objective of this paper is to develop methodology that can recognize the Lanna handwritten character on historical documents by using character feature extraction technique. Historical documents are national treasures. Insignificant effort has been made to preserve Lanna historical documents. Other nations such as Egypt, China and Greece are investing a large effort in restoring and preserving their national historical documents. As a starting point, the focus is on using one Lanna historical document for performing experiments and verifying recognition methods available in this research area. The proposed system consists of three modules, which are image preprocessing module, feature extraction module and character recognition module. The details of each module are following: first, the input image is transformed into a suitable image for feature extraction module. Second, the proposed system extracts character features from the image. Finally, the extracted character information, which is kept in form of bit string, is calculated a similarity value for recognition result. The experiment was conducted on more than 4,000 Lanna handwritten characters by using 10-fold cross-validation classification method which is using 3,600 for training characters and 400 for testing character. The cross-validation process is repeated 10 times, with each of the 10 subsets used exactly once as the validation data. The precision of the proposed system is around 89.73 percent.

show abstract

Section: Background Materialsmentioning

confidence: 99%

Lanna Handwritten Character Recognition on Historical Documents Using Feature Extraction

Khankasikam

2012

AMM

View full text Add to dashboard Cite

show abstract

“…Among the papers concerning Thai handwritten segmentation, they used the classical approaches to segment character [14], [15], [16] and the demonstrations are based on controlling the writing styles of the writers that is not practical. In addition, all those studies were based on modern Thai language and it is different from ancient Thai language.…”

mentioning

confidence: 99%

Character segmentation from ancient palm leaf manuscripts in Thailand

Chamchong

Fung

2011

Proceedings of the 2011 Workshop on Historical Document Imaging and Processing

View full text Add to dashboard Cite

This paper presents a character segmentation system from ancient palm leaf manuscripts written in ancient Thai language. This aims to develop an automated system for the digitization and processing of ancient manuscripts. In this paper, the preprocessing stage of noise reduction is carried out. An optimal binarization is selected in order to reduce the unrelated noise and background information on the document. The proposed approach can improve the readability of the documents and enable selection of the optimal binarization technique. Text line segmentation is then applied to partial projection profiles, and the characters are separated by using the contour tracing algorithm and a trace of background skeleton. The experiment results have shown that this proposed system can be used to support subsequent steps such as automatic recognition of characters from Thai ancient palm leaf.

show abstract

A combined method of segmentation for connected handwritten on palm leaf manuscripts

Chamchong

Fung

2014

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

View full text Add to dashboard Cite

Thai handwriting legal amounts recognition

Cited by 3 publications

References 4 publications

Lanna Handwritten Character Recognition on Historical Documents Using Feature Extraction

Lanna Handwritten Character Recognition on Historical Documents Using Feature Extraction

Character segmentation from ancient palm leaf manuscripts in Thailand

A combined method of segmentation for connected handwritten on palm leaf manuscripts

Contact Info

Product

Resources

About