Unsupervised categorization of heterogeneous text images based on fractals

Khelifi, Badreddine; Zaghden, Nizar; Alimi, Adel M.; Mullot, Rémy

doi:10.1109/icpr.2008.4761176

Cited by 5 publications

(9 citation statements)

References 11 publications

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“…Some works extract similar classes or fonts within the same image such in [1]. This method is not robust for all classes because there is different noise in the same image and sometimes there are some overlapped classes.…”

Section: Related Workmentioning

confidence: 96%

“…In fact, the CDB applied here is considered as a global approach since it gives indices of the whole image [1].…”

Section: Fractal Dimensionsmentioning

confidence: 99%

“…This method is not robust for all classes because there is different noise in the same image and sometimes there are some overlapped classes. The method proposed in [1] is based only on global approaches by extracting fractal dimensions of each connected components. In [2], the authors present a method based on global and local approaches for the indexation of historical document images problem.…”

Section: Related Workmentioning

confidence: 99%

“…We have calculated fractal dimensions of images by three different methods: dilation method, Differential Box counting (DBC) [1,3] and our own approach (CDB: Comptage de densité par Boîte). We have chosen to calculate fractal dimension for the DBC and CDB method by using five different parameters corresponding to the maximum size box: 10, 15, 20, 30 and 40.…”

Section: Fractal Dimensionsmentioning

confidence: 99%

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Characterization of ancient document images composed by Arabic and Latin scripts

Zaghden

Mullot

Alimi

2011

2011 International Conference on Innovations in Information Technology

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In this paper we characterize Arabic and Latin ancient document images. The main criticism of existing works is that most of them are interested in the characterization of Latin historical documents, and they are up to now no many methods that can perform the discrimination between these different language old document images. Regions of images having the same size (256*256 pixels) were extracted from our heterogeneous base. Fractal dimension method is used to discriminate between ancient Arabic and Latin scripts. We achieve 95.87% accuracy on the discrimination between Arabic and Latin ancient document collections. The main advantage of our approach is that it can be easily adapted for the identification of other ancient document collections and we can have better recognition rates by adding relative features of each document base. The encouraging and promising results lead us to study the retrieval of ancient images based on the same technique in order to retrieve similar collections to the image request.

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Section: Related Workmentioning

confidence: 96%

“…In fact, the CDB applied here is considered as a global approach since it gives indices of the whole image [1].…”

Section: Fractal Dimensionsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Fractal Dimensionsmentioning

confidence: 99%

See 2 more Smart Citations

Characterization of ancient document images composed by Arabic and Latin scripts

Zaghden

Mullot

Alimi

2011

2011 International Conference on Innovations in Information Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Sunil et.al [30] proposed a scheme for the extraction of textual areas from an image using Globally Matched Wavelet Filters(GMW) filters with Fisher classifiers.GMW filters was estimated using clustering-based technique. They have used these filters to segment the document images and classify them into text, background, and picture components.…”

Section: Heterogeneous Text Imagesmentioning

confidence: 99%