Recognition of unconstrained handwritten numeral strings by composite segmentation method

Kim, Kye Kyung; Kim, Jin Ho; Suen, C.Y.

doi:10.1109/icpr.2000.906144

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…However, it requires a large dictionary for recognition. Different distance metrics to compute the distance between CCs (Euclidean distance, Convex hull, bounding box, average run length) have been proposed for word segmentation in handwritten [129]- [131] documents. Recognition-based approaches have been proposed for printed [132], handwritten documents [130], [133].…”

Section: Game Theorymentioning

confidence: 99%

“…Flooding the morphological surface and segmenting the input into catchment and basin: Pri, handwritten [128] Hybrid Combination of above approaches: Hist [141] Script-specific: Hist [112], [114], [115], [119], [129], [141], [142], Urdu [143], Persian [109], Chinese [124], [126], English [144], [145] Brahmi: Hw Devanagari [142], Pri Devanagari [146], Bangla [147], Gurmukhi [111] Word Segmentation Distance metric Different metrics to compute the distance between CCs (Euclidean distance, Convex hull, bounding box, average run length): Hw [129]- [131] Recognition Feedback from recognition system; Finds word boundaries based on classification algorithms (Scale space, k-means clustering, Hough transform): Pri [132], Hw [130],…”

Section: Watershedmentioning

confidence: 99%

See 1 more Smart Citation

Document Analysis and Recognition: A survey

NIGAM¹,

Verma²,

Nagabhushan³

2023

Preprint

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<p>The journey of research for Document Analysis and Recognition (DAR) started with the problem of automatic character recognition. Today, it has covered a vast span of recognition tasks such as text recognition, script identification, writer identification, word spotting, signature verification etc., in scripts like Roman, Arabic, Chinese, Japanese, Brahmi etc. Extensive advancements in deep learning techniques have achieved state-of-the-art results for various DAR tasks. This work explores the challenges from different perspectives and reviews the techniques for online/offline and printed/handwritten DAR tasks. We examine the research works with the view of script-related challenges. Various datasets for DAR are categorized into historic, printed and handwritten datasets. We present a comprehensive survey of challenges, techniques, datasets, evaluation metrics, script-related perspectives and potential future directions for DAR.</p>

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Section: Game Theorymentioning

confidence: 99%

Section: Watershedmentioning

confidence: 99%

Document Analysis and Recognition: A survey

NIGAM¹,

Verma²,

Nagabhushan³

2023

Preprint

View full text Add to dashboard Cite

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Notice of Violation of IEEE Publication Principles - An pproach to recognize handwritten bengali numerals for postal automation

Rahman

Rahaman

Ahmed

et al. 2008

2008 11th International Conference on Computer and Information Technology

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Recognition of unconstrained handwritten numeral strings using decision value generator

Kim

Chung²,

Kim³

et al.

Proceedings of Sixth International Conference on Document Analysis and Recognition

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This paper presents recognition of unconstrained handwritten numeral strings using decision value generator. The numeral string recognition system is composed of three modules, pre-segmentation, segmentation and recognition. The pre-segmentation module classifies a numeral string into sub-images, such as isolated digits, touching digits or broken digits, based on the confidence value of decision value generator. The segmentation module splits the touching digits using the reliability value of decision value generator. Both segmentation-based and segmentation-free methods are used in classification and Segmentation. To evaluate the proposed method, experiments have been conducted using the handwritten numeral strings of NIST SDI9 and higher recognition perlformance than previous works has been obtained.

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Recognition of unconstrained handwritten numeral strings by composite segmentation method

Cited by 6 publications

References 5 publications

Document Analysis and Recognition: A survey

Document Analysis and Recognition: A survey

Notice of Violation of IEEE Publication Principles - An pproach to recognize handwritten bengali numerals for postal automation

Recognition of unconstrained handwritten numeral strings using decision value generator

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