The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to be extracted where the variations occur in an image. To find the interest point, Wavelet based Salient Point detector is used. Local Steering Kernel is then applied to the resultant pixels, in ...

Abstract Smoothing images, especially with rich texture, is an important problem in computer vision. Obtaining ideal result difficult due to complexity, irregularity, and anisotropicity of the texture. Besides, some properties are shared by texture structure image. It a hard compromise retain simultaneously remove To create algorithm for image smoothing, we face three problems. For images textu...

We propose a bootstrap sampling method jackboot sampling This provides more accu rate inferences than ordinary bootstrap sampling better con dence interval coverage and less biased or unbiased standard errors The method is simple to implement We also prescribe a smoothing parameter for use in smoothed bootstrapping using or dinary kernel smoothing The e ect is similar to that of jackboot sampling