Image edge detection based on a spatial autoregressive bootstrap approach

Abstract

In this paper a new algorithm to perform edge detection based on a bootstrap approach is presented. This approach uses the estimated spatial conditional distribution of the pixels conditioned by their neighbors. The proposed algorithm approximates the original image by adjusting local 2D autoregressive models to different blocks of the image. The residuals are used in order to generate resampled images by using bootstrap techniques. The proposed algorithm applied to synthetic and real images generates as a result, a binary image, in which the detected edges can be observed.