OVERSEGMENTATION REDUCTION BY FLOODING REGIONS AND DIGGING WATERSHED LINES

Author:

FRUCCI MARIA1

Affiliation:

1. Institute of Cybernetics "E.Caianiello", National Research Council of Italy, Via Campi Flegrei 34 — 80078 Pozzuoli, Napoli, Italy

Abstract

The watershed transformation is a primary tool for segmenting a grey-tone image into subsets that are of interest to a visual observer. The resulting image, however, may often appear oversegmented into a large number of tiny regions (basins), most of which are not significant to the problem of domain. In this paper, a method for removing these nonsignificant basins is presented. The notions of relative significance and intrinsic significance are introduced, which lead to the definition of three types of significance for a basin: strong, weak and partial. The merging of a basin with other basins only occurs when the significance of the basin is not strong, and is restricted to suitably selected adjacent basins. The merging is performed by using an iterated process consisting of two phases. The first involves the removal of certain regional minima, and is accomplished by following either a flooding or a digging scheme. The second identifies the basins corresponding to the regional minima remaining in the image and utilizes the watershed transformation. An appropriate selection of the basins to be merged produces a segmented image perceptually close to the original image. The performance of the proposed method is for the case of astronomic images.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference13 articles.

1. Seeded region growing

2. S. Beucher and F. Meyer, Mathematical Morphology in Image Processing, ed. E. R. Dougherty (Dekker, NY, 1993) pp. 433–481.

3. Watershed-Based Segmentation and Region Merging

4. Image segmentation techniques

Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3