Eriksson, Mats
- Centre for Image Analysis, Sveriges lantbruksuniversitet
Sammanfattning
Two different techniques of performing preprocessing of an image to improve segmentation results are presented. The methods use the grey level thickness of the objects, in order to find the resulting image, by varying the size of a neighbourhood depending on the sum of the included grey levels. The first method, RW, uses the random walk of a particle, defined in the neighbourhood of the position of the particle. The resulting image holds the number of times the particle visits a pixel. Instead of randomization to find the number of visits, the second method, IP, scans the image iteratively and calculates the expected value of the same number. Three different kinds of real world applications are demonstrated to get better segmentation results with the preprocessing techniques included than without. (c) 2005 Elsevier B.V. All rights reserved.
Nyckelord
preprocessing; segmentation; random walk; grey level thickness
Publicerad i
Pattern Recognition Letters
2006, volym: 27, nummer: 3, sidor: 160-166
Utgivare: ELSEVIER SCIENCE BV
SLU författare
UKÄ forskningsämne
Datorgrafik och datorseende
Publikationens identifierare
- DOI: https://doi.org/10.1016/j.patrec.2005.07.010
Permanent länk till denna sida (URI)
https://res.slu.se/id/publ/15117