Optimum Image Filtering Algorithm Over The Unit Sphere
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 9
Abstract
A statistical shape model, which includes a network of deformable curves on the unit sphere as reference framework for seeking geometric features such as high curvature regions and labels such features via a deformation process is confined within a spherical map of the outer surface boundary. The mapping problem of spherical coordinate system, which include discontinuities at the poles and non uniform sampling, are overcome by defining the statistical shape variation in terms of projections of landmark points onto corresponding tangent planes of the sphere. The edge of an image describes the boundary between an object and the background. It represents a sudden change in the value of the image intensity function. So an edge separates two regions of different intensities. However all the edges in an image are not due to the change in intensity values, where parameters like poor focus or refraction can result in edge in an image [1]. The shape of edges in an image depends on different attributes like, lighting conditions, the noise level, type of material and the geometrical and optical properties of the object [2]. Gradient operators of first derivative like Sobel, Prewitt, Roberts and second derivative like Laplacian are used to find the edge in an image [3, 4, 6, 22, 25]. The efficient edge detection operator is evaluated subjectively by visually comparing the output images obtained with certain characteristics [5].
Authors and Affiliations
Er. Pradeep Kumar Jaswal
Keywords
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