A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Surrogate data: A novel approach to object detection
2010
International Journal of Applied Mathematics and Computer Science
Surrogate data: A novel approach to object detection In the present study a novel method is introduced to detect meaningful regions of a gray-level noisy images of binary structures. The method consists in generating surrogate data for an analyzed image. A surrogate image has the same (or almost the same) power spectrum and histogram of gray-level values as the original one but is random otherwise. Then minmax paths are generated in the original image, each characterized by its length, minmax
doi:10.2478/v10006-010-0040-4
fatcat:2qhdiezykvdztkft5j5xzd5wsq