Publication | Closed Access
Three decision levels strategy for Arabic and Latin texts differentiation in printed and handwritten natures
24
Citations
13
References
2007
Year
Artificial IntelligenceEngineeringHandwritingBiometricsHandwritten Latin ScriptsScripting LanguageArabic OrthographyWriter IdentificationIntelligent SystemsGraphologyLatin Texts DifferentiationLanguage DocumentationData ScienceArabicPattern RecognitionData MiningComputational LinguisticsHandwritten NaturesLanguage StudiesCharacter RecognitionOwn Features VectorDecision Levels StrategyOptical Character RecognitionMorphologyComputer ScienceLatin Script IdentificationLinguisticsDocument Processing
Arabic and Latin script identification in printed and handwritten nature present several difficulties because the Arabic (printed or handwritten) and the handwritten Latin scripts are cursive scripts of nature. To avoid all possible confusions which can be generated, we propose in this paper a strategy which is based on three decision levels where each level will have its own features vector and will consist in identifying only one script among the scripts to identify.
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