Greenery and non-greenery image classification using adaptive neuro-fuzzy inference system

被引：1
|
作者：
Balarnurugan, P. [1 ]
Rajesh, R. [1 ]
机构：
[1] Bharathiar Univ, Dept Comp Sci & Engn, Coimbatore 46, Tamil Nadu, India
来源：
ICCIMA 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, VOL III, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/ICCIMA.2007.302
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents greenery and non-greenery image classification using adaptive neuro fuzzy inference systenm. A hybrid set of parameters involving texture and a measure of color coherence using guided (template) image, are used for the purpose of classification. These hybrid set of parameters provide good classification accuracy for greenery and non-greenery images. The performance of the systenm is illustrated with a set of 200 images containing both greenery and non-greenery images.
引用
收藏
页码：431 / 435
页数：5
相关论文
共 50 条
  • [1] Adaptive Neuro-Fuzzy Inference System for Texture Image Classification
    Kuncoro, B. Ari
    Suharjito
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTOMATION, COGNITIVE SCIENCE, OPTICS, MICRO ELECTRO-MECHANICAL SYSTEM, AND INFORMATION TECHNOLOGY (ICACOMIT), 2015, : 196 - 200
  • [2] Adaptive Neuro-Fuzzy Inference System for Classification of Texts
    Kamil, Aida-zade
    Rustamov, Samir
    Clements, Mark A.
    Mustafayev, Elshan
    [J]. RECENT DEVELOPMENTS AND THE NEW DIRECTION IN SOFT-COMPUTING FOUNDATIONS AND APPLICATIONS, 2018, 361 : 63 - 70
  • [3] Adaptive Neuro-Fuzzy Inference System for Non-linear Classification Problem of Theobroma cacao Image
    Prilianti, Kestrilia Rega
    Setiawan, Hendry
    Adhiwibawa, Marcelinus Alfasisurya Setya
    Anita-Sari, Indah
    Anam, Syaiful
    Brotosudarmo, Tatas Hardo Panintingjati
    [J]. ROMANIAN JOURNAL OF INFORMATION SCIENCE AND TECHNOLOGY, 2019, 22 (3-4): : 272 - 283
  • [4] Bayesian inference using an adaptive neuro-fuzzy inference system
    Knaiber, Mohammed
    Alawieh, Leen
    [J]. FUZZY SETS AND SYSTEMS, 2023, 459 : 43 - 66
  • [5] Adaptive neuro-fuzzy inference system for classification of ECG signal
    [J]. 1600, IEEE Computer Society
  • [6] Adaptive Neuro-Fuzzy Inference System for Classification of ECG Signal
    Muthuvel, K.
    Suresh, L. Padma
    [J]. PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON CIRCUITS, POWER AND COMPUTING TECHNOLOGIES (ICCPCT 2013), 2013, : 1162 - 1166
  • [7] GPS Signal Reception Classification Using Adaptive Neuro-Fuzzy Inference System
    Sun, Rui
    Hsu, Li-Ta
    Xue, Dabin
    Zhang, Guohao
    Ochieng, Washington Yotto
    [J]. JOURNAL OF NAVIGATION, 2019, 72 (03): : 685 - 701
  • [8] Adaptive neuro-fuzzy inference system for classification of mammographic image using electromagnetism-like optimisation
    Vimalkumar, M. N.
    Helenprabha, K.
    [J]. INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY, 2018, 26 (3-4) : 376 - 384
  • [9] Image Interpolation Based on Adaptive Neuro-Fuzzy Inference System
    Maleki, Shiva Aghapour
    Tinati, Mohammad Ali
    Tazehkand, Behzad Mozaffari
    [J]. 2019 3RD INTERNATIONAL CONFERENCE ON IMAGING, SIGNAL PROCESSING AND COMMUNICATION (ICISPC), 2019, : 78 - 84
  • [10] Automatic Classification of Antepartum Cardiotocography Using Fuzzy Clustering and Adaptive Neuro-Fuzzy Inference System
    Fei, Yue
    Huang, Xiaoqian
    Chen, Qinqun
    Chen, Jiamin
    Li, Li
    Hong, Jiaming
    Hao, Zhifeng
    Wei, Hang
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, 2020, : 1938 - 1942
12345