Share Email Print

Optical Engineering

Block-based unsupervised natural image segmentation
Author(s): Chee Sun Won
Format Member Price Non-Member Price
PDF $20.00 $25.00

Paper Abstract

We propose a block-based unsupervised image segmentation algorithm in which the basic unit for the region labeling is an image block rather than a pixel. Adopting the image block, we can introduce a new paradigm for the unsupervised image segmentation, namely, an edge-and-region based segmentation. That is, in our block-based segmentation, we exploit both edge blocks in the region boundary and the homogeneous blocks inside the region. The interior texture and monotone blocks are used to identify regions and the edge blocks are used to find an accurate contour. To obtain a pixel level segmentation, we divide the edge and unlabeled blocks into quadrant and relabel those subblocks to one of the neighboring homogeneous regions. We repeat this process until we obtain a pixel-based segmentation. Experimental results show that the proposed segmentation yields accurate segmentation for natural images even if they contain some texture regions as well as monotone regions.

Paper Details

Date Published: 1 December 2000
PDF: 8 pages
Opt. Eng. 39(12) doi: 10.1117/1.1321198
Published in: Optical Engineering Volume 39, Issue 12
Show Author Affiliations
Chee Sun Won, Dongguk Univ. (South Korea)

© SPIE. Terms of Use
Back to Top