Naeemullah Khan

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We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across(More)
We formulate a general energy and method for segmentation that is designed to have preference for segmenting the coarse structure over the fine structure of the data, without smoothing across boundaries of regions. The energy is formulated by considering data terms at a continuum of scales from the scale space computed from the Heat Equation within regions,(More)
The causes of night blindness in children are multifactorial and particular consideration has been given to childhood nutritional deficiency, which is the most common problem found in underdeveloped countries. Such deficiency can result in physiological and pathological processes that in turn influence biological sample composition. This study was designed(More)
An innovative, rapid, and simple dual-dispersive liquidߛliquid microextraction (DDLL-ME) approach was used to extract uranium from real samples for the first time. The main objective of this study was to disperse extraction solvent by using an air-agitated syringe system to overcome matrix effects and avoid dispersion of hazardous dispersive organic(More)
A simple and rapid dispersive liquid-liquid microextraction procedure based on ionic liquid assisted microemulsion (IL-µE-DLLME) combined with cloud point extraction has been developed for preconcentration copper (Cu(2+)) in drinking water and serum samples of adolescent female hepatitits C (HCV) patients. In this method a ternary system was developed to(More)
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