Niraj P. Doshi

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Texture recognition is an important aspect of many computer vision applications. Local binary pattern (LBP) based texture algorithms have gained significant popularity in recent years and have been shown to be useful for a variety of tasks. While over the years a variety of LBP algorithms have been introduced in the literature, what is missing is a(More)
Nailfold capillaroscopy (NC) is a non-invasive imaging technique employed to assess the condition of blood capillaries in the nailfold. It is particularly useful for early detection of scleroderma spectrum disorders and evaluation of Raynaud's phenomenon. While diagnosis based on NC is typically performed by manual inspection, computerised nailfold(More)
Texture analysis and classification play an important role in many multimedia and computer vision applications. Local binary patterns (LBP) form a simple yet powerful texture descriptor characterising local neighbourhood properties, and consequently LBP variants are widely employed. In this paper, we demonstrate that through appropriate construction of a(More)
Nailfold capillaroscopy (NC) is a non-invasive imaging technique employed to assess the condition of blood capillaries in the nailfold. It is particularly useful for early detection of scleroderma spectrum disorders and evaluation of Raynaud's phenomenon. While diagnosis based on NC is typically performed by manual inspection, computerised nailfold(More)
Texture classification is an important task for a variety of computer vision applications. A successful group of texture algorithms based on local neighbourhood descriptors and known as LBP (local binary patterns) has been shown to provide good and robust discriminative power, and is typically applied in a rotation invariant form and calculated at multiple(More)
Local binary patterns (LBP) are known as a simple yet powerful texture descriptor encoding local neighbourhood properties. LBP descriptors can be calculated at different radii, leading to a multi-resolution texture characterisation. Multi-dimensional LBP (MD-LBP) utilises this concept, while also maintaining the relationships between the different scales by(More)