A Segmentation Scheme Based on a Multi-graph Representation: Application to Colour Cadastral Maps

被引:0
|
作者
Raveaux, Romain
Burie, Jean-Christophe
Ogier, Jean-Marc
机构
来源
GRAPHICS RECOGNITION: RECENT ADVANCES AND NEW OPPORTUNITIES | 2008年 / 5046卷
关键词
Colour Segmentation; Colour Space; Graphics Recognition; Document Understanding;
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
In this paper, a colour segmentation process is proposed. The novelty relies on an efficient way to introduce a priori knowledge to isolate pertinent re-ions. Basically. from a pixel classification stage a Suitable colour model is set up. A hybrid colour space is built by choosing meaningful components from several standard colour representations. Thereafter, a segmentation algorithm is performed. The region extraction is executed by a vectorial gradient dealing with hybrid colour space. From this point, a merging mechanism is carried Out. It is based on a multi-graphs data structure where each graph represents a different point of view of the region layout. Hence. merging decisions can be taken considering graph information and according to a set of applicative rules. The whole system is assessed oil ancient cadastral maps and experiments tend to reveal a reliable behaviour in term of Information retrieval.
引用
收藏
页码:202 / 212
页数:11
相关论文
共 50 条
  • [31] Human action recognition based on the Grassmann multi-graph embedding
    Sahere Rahimi
    Ali Aghagolzadeh
    Mehdi Ezoji
    Signal, Image and Video Processing, 2019, 13 : 271 - 279
  • [32] Optimizing multi-graph learning based salient object detection
    Li, Shiqi
    Zeng, Cheng
    Fu, Yan
    Liu, Shiping
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2017, 55 : 93 - 105
  • [33] Human action recognition based on the Grassmann multi-graph embedding
    Rahimi, Sahere
    Aghagolzadeh, Ali
    Ezoji, Mehdi
    SIGNAL IMAGE AND VIDEO PROCESSING, 2019, 13 (02) : 271 - 279
  • [34] Embedded Multi-View Clustering via Collaborative Tensor Subspace Representation and Multi-Graph Fusion
    Wang, Jingyu
    Deng, Tingquan
    Yang, Ming
    Wang, Jiayi
    IEEE SIGNAL PROCESSING LETTERS, 2025, 32 : 911 - 915
  • [35] A colour text/graphics separation based on a graph representation
    Raveaux, Romain
    Burie, Jean-Christophe
    Ogier, Jean-Marc
    19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, : 2080 - 2083
  • [36] Image emotion multi-label classification based on multi-graph learning
    Wang, Meixia
    Zhao, Yuhai
    Wang, Yejiang
    Xu, Tongze
    Sun, Yiming
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 231
  • [37] MGREL: A multi-graph representation learning-based ensemble learning method for gene-disease association prediction
    Wang, Ziyang
    Gu, Yaowen
    Zheng, Si
    Yang, Lin
    Li, Jiao
    COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 155
  • [38] Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning
    Wang, Runzhong
    Yan, Junchi
    Yang, Xiaokang
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 33, NEURIPS 2020, 2020, 33
  • [39] Unsupervised multi-graph propagation for ranking based on order change tendency
    Liu, Jin-Li
    Zheng, Nan
    Xie, Mao-Qiang
    Huang, Ya-Lou
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 2683 - 2689
  • [40] Group vehicle trajectory prediction model based on multi-graph fusion
    Sang, Haifeng
    Li, Siyu
    Wang, Jinyu
    Chen, Wangxing
    Zhao, Zishan
    COMPUTERS & ELECTRICAL ENGINEERING, 2025, 123