Image segmentation via local higher order statistics | Zendy

Farhadi Ali | Zendy; Shahshahani Mehrdad | Zendy

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Image segmentation via local higher order statistics

Author(s) -

Farhadi Ali,

Shahshahani Mehrdad

Publication year - 2003

Publication title -

international journal of imaging systems and technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.359

H-Index - 47

eISSN - 1098-1098

pISSN - 0899-9457

DOI - 10.1002/ima.10069

Subject(s) - segmentation , artificial intelligence , pixel , computer science , image segmentation , scale space segmentation , texture (cosmology) , pattern recognition (psychology) , image (mathematics) , image texture , computer vision , segmentation based object categorization , order (exchange) , economics , finance

The aim of this work is to present a method for the segmentation of images based on local higher order statistics. The algorithm can be applied for the separation of objects from a texture background and the segmentation of textures. The proposed technique makes no use of a data bank and its complexity is O ( ) where is the number of pixels. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol 13, 215–223, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10069

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