Integrated segmentation and recognition of connected Ottoman script

Yalnız, İsmet Zeki; Altıngövde, İsmail Sengör; Güdükbay, Uğur; Ulusoy, Özgür

doi:10.1117/1.3262346

Cited by 14 publications

(14 citation statements)

References 27 publications

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“…Yalniz et al [46,47] also exploited graph matching and chain code matching methods in their study for retrieval of Ottoman documents, but there are some differences between our method and theirs. In [46], they said that after thinning, a refinement could also be performed to reduce the number of nodes, but this was not necessary in their case since they did not use a graph-matching algorithm, and in [47], character graphs are compared by extracting a number of features from the graphs and calculating an overall similarity score by weighting the similarity scores between corresponding features of the graphs.…”

Section: Sub-pattern Matchingmentioning

confidence: 99%

“…In [46], they said that after thinning, a refinement could also be performed to reduce the number of nodes, but this was not necessary in their case since they did not use a graph-matching algorithm, and in [47], character graphs are compared by extracting a number of features from the graphs and calculating an overall similarity score by weighting the similarity scores between corresponding features of the graphs. On the other hand in our study, we match extracted graphs by isomorphism.…”

Section: Sub-pattern Matchingmentioning

confidence: 99%

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Matching Islamic patterns in Kufic images

Arifoǧlu

Sahin

Adiguzel

et al. 2015

Pattern Anal Applic

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In this study, we address the problem of matching patterns in Kufic calligraphy images. Being used as a decorative element, Kufic images have been designed in a way that makes it difficult to be read by non-experts. Therefore, available methods for handwriting recognition are not easily applicable to the recognition of Kufic patterns. In this study, we propose two new methods for Kufic pattern matching. The first method approximates the contours of connected components into lines and then utilizes chain code representation. Sequence matching techniques with a penalty for gaps are exploited for handling the variations between different instances of sub-patterns. In the second method, skeletons of connected components are represented as a graph where junction and end points are considered as nodes. Graph isomorphism techniques are then relaxed for partial graph matching. Methods are evaluated over a collection of 270 square Kufic images with 8,941 sub-patterns. Experimental results indicate that, besides retrieval and indexing of known patterns, our method also allows the discovery of new patterns.

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Section: Sub-pattern Matchingmentioning

confidence: 99%

Section: Sub-pattern Matchingmentioning

confidence: 99%

Matching Islamic patterns in Kufic images

Arifoǧlu

Sahin

Adiguzel

et al. 2015

Pattern Anal Applic

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“…Rare words may not be included in the vocabulary. Moreover, broader vocabulary may also degrade the system performance significantly [Yalniz et al 2009]. Examples of segmentationfree systems include Ataer and Duygulu [2006;2007].…”

Section: 14mentioning

confidence: 99%

“…Image segmentation, normalization, and edge detection stages are employed for feature extraction. In a recent work [Yalniz et al 2009], segmentation and recognition stages are integrated for recognizing Ottoman script so that the weaknesses of the classifier can be compensated for by taking into account possible character sequences for a particular connected component. The sequence of candidate characters that formulates a connected component is found by tracing the longest path over the acyclic graph constructed for the bigram approximation of the score function.…”

Section: Character Recognition and Automatic Retrieval For Ottoman Domentioning

confidence: 99%

Ottoman archives explorer

Yalnız

Altıngövde

Güdükbay

et al. 2009

J. Comput. Cult. Herit.

Self Cite

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This article presents Ottoman Archives Explorer, a Content-Based Retrieval (CBR) system based on character recognition for printed and handwritten historical documents. Several methods for character segmentation and recognition stages are investigated. In particular, sliding-window and histogram segmentation methods are coupled with recognition approaches using spatial features, neural networks, and a graph-based model. The prototype system provides CBR of document images using both example-based queries and a virtual keyboard to construct query words.

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“…these documents 2 , however there is a lack of resources for analysis and translation except a few recent attempts [6,7,12,13,52,62,63].…”

mentioning

confidence: 99%

Cross-document word matching for segmentation and retrieval of Ottoman divans

Duygulu

Arifoǧlu

Kalpaklı

2014

Pattern Anal Applic

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Cataloged from PDF version of article.Motivated by the need for the automatic\ud indexing and analysis of huge number of documents in\ud Ottoman divan poetry, and for discovering new knowledge\ud to preserve and make alive this heritage, in this study we\ud propose a novel method for segmenting and retrieving\ud words in Ottoman divans. Documents in Ottoman are dif-\ud ficult to segment into words without a prior knowledge of\ud the word. In this study, using the idea that divans have\ud multiple copies (versions) by different writers in different\ud writing styles, and word segmentation in some of those\ud versions may be relatively easier to achieve than in other\ud versions, segmentation of the versions (which are difficult,\ud if not impossible, with traditional techniques) is performed\ud using information carried from the simpler version. One\ud version of a document is used as the source dataset and the\ud other version of the same document is used as the target\ud dataset. Words in the source dataset are automatically\ud extracted and used as queries to be spotted in the target\ud dataset for detecting word boundaries. We present the idea\ud of cross-document word matching for a novel task of\ud segmenting historical documents into words. We propose a\ud matching scheme based on possible combinations of\ud sequence of sub-words. We improve the performance of\ud simple features through considering the words in a context.\ud The method is applied on two versions of Layla and\ud Majnun divan by Fuzuli. The results show that, the proposed\ud word-matching-based segmentation method is\ud promising in finding the word boundaries and in retrieving\ud the words across documents

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Integrated segmentation and recognition of connected Ottoman script

Cited by 14 publications

References 27 publications

Matching Islamic patterns in Kufic images

Matching Islamic patterns in Kufic images

Ottoman archives explorer

Cross-document word matching for segmentation and retrieval of Ottoman divans

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