An algorithm for object extraction in a random field background using a multiresolution pyramid based on a modified weighted pixel linking model is described. The original model'' depends on the geometric distances node-father and on a density distribution function of the node''s sons characteristics for extracting compact objects. A k parameter was additioned to the Gaussian distribution function that allows a better fit for the objects to be recognized. The gray levels standard deviation (s. d. ) of the objects in the original image can have an important role in the segmentation process for selecting the parameters needed to clean the histogram of the segmented image of the natural texture and noisy regions. The results were applied to the extraction of a characteristic defect of a cork agglomerate tile.

Date Published: 1 November 1990
PDF: 10 pages
Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); doi: 10.1117/12.23538

Published in SPIE Proceedings Vol. 1349:
Applications of Digital Image Processing XIII
Andrew G. Tescher, Editor(s)