New Rotation-Invariant Texture Analysis Technique Using Radon Transform and Hidden Markov Models

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概要

• 論文の詳細を見る

• A rotation invariant texture analysis technique is proposed with a novel combination of Radon Transform (RT) and Hidden Markov Models (HMM). Features of any texture are extracted during RT which due to its inherent property captures all the directional properties of a certain texture. HMMs are used for classification purpose. One HMM is trained for each texture on its feature vector which preserves the rotational invariance of feature vector in a more compact and useful form. Once all the HMMs have been trained, testing is done by picking any of these textures at any arbitrary orientation. The best percentage of correct classification (PCC) is above 98 % carried out on sixty texture of Brodatz album.

• （社）電子情報通信学会の論文
• 2008-12-01

著者

• JALIL ABDUL

  Department of Biochemistry, Kagoshima University Graduate School of Medical and Dental Sciences

• Qureshi Ijaz

  Centre Of Intelligent Systems Engineering Iiui

• Jalil Abdul

  Iiu Islamabad Pak

• Jalil Abdul

  Department Of Biochemistry Kagoshima University Graduate School Of Medical And Dental Sciences

• MANZAR Anwar

  Centre of Intelligent Systems Engineering IIUI

• CHEEMA Tanweer

  Centre of Intelligent Systems Engineering IIUI

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• New Rotation-Invariant Texture Analysis Technique Using Radon Transform and Hidden Markov Models

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