A new Automatic Seeded Region Growing Algorithm

被引:0
|
作者
Li, Chonglun [1 ]
Yang, Lujing [1 ]
Liu, Zhong [1 ]
Li, Ke [1 ]
机构
[1] Naval Univ Engn, Coll Elect Engn, Wuhan, Peoples R China
关键词
region growing; explorer; segmentation; Multi-threshold; NUMERICAL-SIMULATION; SEGMENTATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Generally speaking, the object well dealt by region growing algorithm does not have clear boundary or gradient regularization. Therefore, the explorer method is proposed in this paper, which makes it possible to obtain a seed region following the rapidly self-adapting multi-threshold segmentation. Each boundary pixel is regarded as an encampment, which can send four explorers to its four neighbors. In the particular case of coordination between the encampments, every explorer with its limited supplies, according to the rule, can supplement its consumption and then overcome the block created by the differential value of grayness between the pixels. In the course of iteration, the segmentation of images can be fulfilled. The measurement and test of a series of standard images shows that the method is practicable and effective in the segmentation of an object image.
引用
下载
收藏
页码:543 / 549
页数:7
相关论文
共 50 条
  • [21] Affinity Based Seeded Region Growing Algorithm For Medical Image Segmentation
    Nagaraju, S.
    Kashyap, Manish
    Kumar, Sandeep
    Bhattacharya, Mahua
    2015 INTERNATIONAL CONFERENCE ON COMPUTING AND NETWORK COMMUNICATIONS (COCONET), 2015, : 725 - 730
  • [22] A smoke segmentation algorithm based on improved intelligent seeded region growing
    Zhao, Wangda
    Chen, Weixiang
    Liu, Yujie
    Wang, Xiangwei
    Zhou, Yang
    FIRE AND MATERIALS, 2019, 43 (06) : 725 - 733
  • [23] Segmentation of Extrapulmonary Tuberculosis Infection Using Modified Automatic Seeded Region Growing
    Avazpour, Iman
    Saripan, M. Iqbal
    Nordin, Abdul Jalil
    Abdullah, Raja Syamsul Azmir Raja
    BIOLOGICAL PROCEDURES ONLINE, 2009, 11 (01) : 241 - 252
  • [24] COMPARATIVE STUDY OF COLOR IMAGE SEGMENTATION BY THE SEEDED REGION GROWING ALGORITHM
    Charifi, Rajaa
    Essbai, Najia
    Mansouri, Anass
    Zennayi, Yahya
    2018 IEEE 5TH INTERNATIONAL CONGRESS ON INFORMATION SCIENCE AND TECHNOLOGY (IEEE CIST'18), 2018, : 279 - 284
  • [25] Automatic Polling Seeded Region Growing (APSRG) for Segmentation of Blood Vessels in Fundus
    Rahayu, Putri Nur
    Permadi, Dimas Fanny Hebrasianto
    Erwanto, Danang
    2022 2ND INTERNATIONAL CONFERENCE ON INTELLIGENT CYBERNETICS TECHNOLOGY & APPLICATIONS (ICICYTA), 2022, : 180 - 185
  • [26] Automatic region growing algorithm for the visible human dataset
    Jones, FS
    Arabnia, H
    CISST'03: PROCEEDING OF THE INTERNATIONAL CONFERENCE ON IMAGING SCIENCE, SYSTEMS AND TECHNOLOGY, VOLS 1 AND 2, 2003, : 665 - 672
  • [27] Automatic Segmentation of DNA Microarray Images Using an Improved Seeded Region Growing Method
    Deepa, J.
    Thomas, Tessamma
    2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009), 2009, : 1468 - 1473
  • [28] Anisotropic Diffusion with Morphological Reconstruction and Automatic Seeded Region Growing for Color Image Segmentation
    Yang, Ha-Hong
    Liu, Jie
    Zhong, Tan-Cheng
    ISISE 2008: INTERNATIONAL SYMPOSIUM ON INFORMATION SCIENCE AND ENGINEERING, VOL 2, 2008, : 591 - 595
  • [29] Automatic image segmentation by integrating color-edge extraction and seeded region growing
    Fan, JP
    Yau, DKY
    Elmagarmid, AK
    Aref, WG
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (10) : 1454 - 1466
  • [30] Image segmentation using automatic seeded region growing and instance-based learning
    Gomez, Octavio
    Gonzalez, Jesus A.
    Morales, Eduardo F.
    PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS, 2007, 4756 : 192 - 201