On boundary pixels in seeded region growing segmentation

被引:1
|
作者
Zhang, MS [1 ]
Huang, J [1 ]
Pawitanm, Y [1 ]
机构
[1] SW Univ Nationalities, Sch Econ & Management, Chengdu 610041, Peoples R China
来源
PARALLEL AND DISTRIBUTED COMPUTING, APPLICATIONS AND TECHNOLOGIES, PDCAT'2003, PROCEEDINGS | 2003年
关键词
image analysis; region growing; segmentation; semiautomatic method;
D O I
10.1109/PDCAT.2003.1236427
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Boundary pixels can have a subtle but serious impact on the performance of the seeded region growing algorithm [1], a fast semi-automatic algorithm for segmentation of intensity images. We have found, however, that as originally described the algorithm can fail if some sections of a connected segment is narrow. The failure results, for example, in a loss of details or an undue dependence of seed placement. The remedy is a careful processing of the boundary pixels. We here present an algorithm whose performance is not affected by such situation.
引用
收藏
页码:838 / 839
页数:2
相关论文
共 50 条
  • [21] Improving Parameters Selection of a Seeded Region Growing Method for Multiband Image Segmentation
    Sanchez, J.
    Martinez, E.
    Arquero, A.
    IEEE LATIN AMERICA TRANSACTIONS, 2015, 13 (03) : 843 - 849
  • [22] Cuckoo Search Based Color Image Segmentation Using Seeded Region Growing
    Preetha, M. Mary Synthuja Jain
    Suresh, L. Padma
    Bosco, M. John
    POWER ELECTRONICS AND RENEWABLE ENERGY SYSTEMS, 2015, 326 : 1573 - 1583
  • [23] 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
  • [24] Genetic based Fuzzy Seeded Region Growing Segmentation for Diabetic Retinopathy Images
    Tamilarasi, M.
    Duraiswamy, K.
    2013 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS, 2013,
  • [25] Medical image segmentation using 3-D seeded region growing
    Justice, RK
    Stokely, EM
    Strobel, JS
    Ideker, RE
    Smith, WM
    IMAGE PROCESSING - MEDICAL IMAGING 1997, PTS 1 AND 2, 1997, 3034 : 900 - 910
  • [26] Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing
    Huang, Zilong
    Wang, Xinggang
    Wang, Jiasi
    Liu, Wenyu
    Wang, Jingdong
    2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, : 7014 - 7023
  • [27] Texture feature based automated seeded region growing in abdominal MRI segmentation
    Wu, Jie
    Poehlman, Skip
    Noseworthy, Michael D.
    Kamath, Markad V.
    BMEI 2008: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOL 2, 2008, : 263 - +
  • [28] 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
  • [29] COLOR IMAGE SEGMENTATION BASED ON SEEDED REGION GROWING WITH CANNY EDGE DETECTION
    Chen Hejun
    Ding Haiqiang
    He Xiongxiong
    Zhuang Hualiang
    2014 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP), 2014, : 683 - 686
  • [30] Regularized seeded region growing
    Beare, R
    MATHEMATICAL MORPHOLOGY, PROCEEDINGS, 2002, : 91 - 99