Interactive max-tree visualization tool for image processing and analysis

被引:0
|
作者
Tavares, Luis A. [1 ,3 ]
Souza, Roberto M. [1 ]
Rittner, Leticia [1 ]
Machado, Rubens C. [2 ]
Lotufo, Roberto A. [1 ]
机构
[1] Univ Estadual Campinas, Sch Elect & Comp Engn, Campinas, SP, Brazil
[2] Ctr Informat Technol Renato Archer CTI, Campinas, SP, Brazil
[3] Fed Inst Educ Sci & Technol South Minas Gerais IF, Pouso Alegre, Brazil
来源
5TH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, THEORY, TOOLS AND APPLICATIONS 2015 | 2015年
关键词
max-tree visualization; interactive max-tree; connected filtering; interactive segmentation; CONCURRENT COMPUTATION; COMPONENT TREE; SEGMENTATION;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The max-tree is a data structure that represents all possible upper thresholds of an image, it has been successfully used in many image processing and analysis applications. The max-tree corresponding to a natural image usually has thousands of nodes, which makes unpractical to build a comprehensive graphical representation of its complete structure. In this paper, we propose a methodology that allows to build an interactive max-tree graphical representation that permits the user to navigate through the max-tree nodes, to visualize its connected components and to create node subsets. Our representation displays a simplified max-tree, but it allows the user to access all max-tree nodes using the interactive features. To the best of our knowledge, this is the first work that proposes an interactive graphical representation of the max-tree. We depict the potential of our max-tree visualization tool for interactive segmentation, connected filtering, and collection of training samples.
引用
收藏
页码:119 / 124
页数:6
相关论文
共 50 条
  • [21] Segmenting Junction Regions Without Skeletonization Using Geodesic Operators and the Max-Tree
    Serna, Andres
    Marcotegui, Beatriz
    Decenciere, Etienne
    MATHEMATICAL MORPHOLOGY AND ITS APPLICATIONS TO SIGNAL AND IMAGE PROCESSING, ISMM 2019, 2019, 11564 : 456 - 467
  • [22] GPT.EXE: A powerful tool for the visualization and analysis of general processing tree models
    Hu, XG
    Phillips, GA
    BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS, 1999, 31 (02): : 220 - 234
  • [23] GPT.EXE: A powerful tool for the visualization and analysis of general processing tree models
    Xiangen Hu
    Glenn A. Phillips
    Behavior Research Methods, Instruments, & Computers, 1999, 31 : 220 - 234
  • [24] Attribute Filtering of Urban Point Clouds Using Max-Tree on Voxel Data
    Guiotte, Florent
    Lefevre, Sebastien
    Corpetti, Thomas
    MATHEMATICAL MORPHOLOGY AND ITS APPLICATIONS TO SIGNAL AND IMAGE PROCESSING, ISMM 2019, 2019, 11564 : 391 - 402
  • [25] Visualization and interactive analysis of multidimensional image data
    Cetin, H
    VISUAL DATA EXPLORATION AND ANALYSIS III, 1996, 2656 : 181 - 188
  • [26] MTStereo 2.0: Accurate Stereo Depth Estimation via Max-Tree Matching
    Brandt, Rafael
    Strisciuglio, Nicola
    Petkov, Nicolai
    COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2021, PT 1, 2021, 13052 : 110 - 119
  • [27] THE SPECTRAL IMAGE-PROCESSING SYSTEM (SIPS) - INTERACTIVE VISUALIZATION AND ANALYSIS OF IMAGING SPECTROMETER DATA
    KRUSE, FA
    LEFKOFF, AB
    BOARDMAN, JW
    HEIDEBRECHT, KB
    SHAPIRO, AT
    BARLOON, PJ
    GOETZ, AFH
    REMOTE SENSING OF ENVIRONMENT, 1993, 44 (2-3) : 145 - 163
  • [28] ProteoViz: a tool for the analysis and interactive visualization of phosphoproteomics data
    Storey, Aaron J.
    Naceanceno, Kevin S.
    Lan, Renny S.
    Washam, Charity L.
    Orr, Lisa M.
    Mackintosh, Samuel G.
    Tackett, Alan J.
    Edmondson, Rick D.
    Wang, Zhengyu
    Li, Hong-yu
    Frett, Brendan
    Kendrick, Samantha
    Byrum, Stephanie D.
    MOLECULAR OMICS, 2020, 16 (04) : 316 - 326
  • [29] CMDnavigator: A tool for interactive analysis and visualization of peptide data
    Bayden, Alexander
    Diller, David
    Audie, Joseph
    Diller, Kyle
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2017, 253
  • [30] ClusterTag: Interactive Visualization, Clustering and Tagging Tool for Big Image Collections
    Pogorelov, Konstantin
    Riegler, Michael
    Halvorsen, Pal
    Griwodz, Carsten
    PROCEEDINGS OF THE 2017 ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL (ICMR'17), 2017, : 112 - 116