A Blur Robust Color Image Dectection Method Based on Maximally Stable Extremal Regions

被引:0
|
作者
Yu, Tong [1 ]
Lu, Chaochao [1 ]
机构
[1] Nanjing Univ, Software Inst, Nanjing, Peoples R China
关键词
MSER; blur; color space; continuous edges; Hysteresis Thresholding;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Maximally Stable Extremal Region (MSER) has been proven to be an excellent feature extraction method in computer vision. However, the initial MSER detector performs not so well in blur situation. Meanwhile, the traditional method is merely applied to intensity space, so that some important color-related information is inevitably overlooked. Hence, this paper utilized the concept of Hysteresis Thresholding to obtain continuous edges information in RGB color channels and extended the original intensity definition and stability criterion of the MSER method in RGB color space with the acquired curves. Result part indicates that in blur and colourful situations, our method performs better compared with the original MSER method and a traditional practice detecting color object based on MSER.
引用
收藏
页码:223 / 226
页数:4
相关论文
共 50 条
  • [1] Entropy-Based Maximally Stable Extremal Regions for Robust Feature Detection
    Cai, Huiwen
    Wang, Xiaoyan
    Xia, Ming
    Wang, Yangsheng
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2012, 2012
  • [2] Maximally Stable Extremal Regions Improved Tracking Algorithm Based on Depth Image
    Wang, Haikuan
    Xie, Dong
    Sun, Haoxiang
    Zhou, Wenju
    [J]. INTELLIGENT COMPUTING AND INTERNET OF THINGS, PT II, 2018, 924 : 546 - 554
  • [3] Pedestrian detection based on maximally stable extremal regions
    Frolov, Vadim
    Leon, Fernando Puente
    [J]. 2010 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2010, : 910 - 914
  • [4] Fast road obstacle detection method based on maximally stable extremal regions
    Xu Yi
    Gao Song
    Tan Derong
    Guo Dong
    Sun Liang
    Wang Yuqiong
    [J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2018, 15 (01):
  • [5] Scene text detection method research based on maximally stable extremal regions
    Xu, Lei
    Liu, Yi
    Mou, Lianming
    [J]. INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS, 2022, 15 (02) : 142 - 154
  • [6] Human Tracking Method Based on Maximally Stable Extremal Regions with Multi-cameras
    Zhang, Li
    Dai, Guojun
    Wang, Changjun
    [J]. FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE, PTS 1-4, 2011, 44-47 : 3681 - 3686
  • [7] Improved maximally stable extremal regions based method for the segmentation of ultrasonic liver images
    Zhu, Haijiang
    Sheng, Junhui
    Zhang, Fan
    Zhou, Jinglin
    Wang, Jing
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2016, 75 (18) : 10979 - 10997
  • [8] Improved maximally stable extremal regions based method for the segmentation of ultrasonic liver images
    Haijiang Zhu
    Junhui Sheng
    Fan Zhang
    Jinglin Zhou
    Jing Wang
    [J]. Multimedia Tools and Applications, 2016, 75 : 10979 - 10997
  • [9] Robust wide-baseline stereo from maximally stable extremal regions
    Matas, J
    Chum, O
    Urban, M
    Pajdla, T
    [J]. IMAGE AND VISION COMPUTING, 2004, 22 (10) : 761 - 767
  • [10] Shape descriptors for maximally stable extremal regions
    Forssen, Per-Erik
    Lowe, David G.
    [J]. 2007 IEEE 11TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1-6, 2007, : 1530 - 1537