Noise Removal and Enhancement of Binary Images Using Morphological Operations

被引:0
|
作者
Jamil, Nursuriati [1 ]
Sembok, Tengku Mohd Tengku [2 ]
Abu Bakar, Zainab [1 ]
机构
[1] Univ Teknol MARA, Fac Informat Technol & Quantitat Sci, Shah Alam 40450, Selangor, Malaysia
[2] Univ Pertahanan, Kuala Lumpur, Malaysia
关键词
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
Mathematical morphological operations are commonly used as a tool in image processing for extracting image components that are useful in the representation and description of region shape. In this paper, six basic morphological operations are investigated to remove noise and enhance the appearance of binary images. Dilation, erosion, opening, closing, fill and majority operations are tested on twenty-five images and subjectively evaluated based on perceived quality of the enhanced images. Results of the experiments showed that noise can be effectively removed from binary images using combinations of erode-dilate operations. Also, the binary images are significantly enhanced using combinations of majority-close operations.
引用
收藏
页码:2838 / +
页数:3
相关论文
共 50 条
  • [1] Noise removal and contrast enhancement in fundus images via morphological operations
    Fleitas Maidana, Maria Belen
    Vazquez Noguera, Jose Luis
    Pinto-Roa, Diego P.
    Cesar Mello-Roman, Julio
    2022 17TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2022,
  • [2] Morphological operations on crack coded binary images
    Wilson, GR
    IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 1996, 143 (03): : 171 - 176
  • [3] Target recognition in synthetic aperture radar images using binary morphological operations
    Ding, Baiyuan
    Wen, Gongjian
    Ma, Conghui
    Yang, Xiaoliang
    JOURNAL OF APPLIED REMOTE SENSING, 2016, 10
  • [4] Clutter noise removal in binary document images
    Mudit Agrawal
    David Doermann
    International Journal on Document Analysis and Recognition (IJDAR), 2013, 16 : 351 - 369
  • [5] Clutter noise removal in binary document images
    Agrawal, Mudit
    Doermann, David
    INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, 2013, 16 (04) : 351 - 369
  • [6] Shadow detection and removal from images using machine learning and morphological operations
    Nair, Vicky
    Ram, Parimala Geetha Kosal
    Sundararaman, Sundaravadivelu
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (01): : 11 - 18
  • [7] A Novel Adaptive Approach to Process Binary Fingerprint Images Using Directional Morphological Operations
    Jin Qi School of Electronic Engineering
    JournalofElectronicScienceandTechnologyofChina, 2009, 7 (02) : 129 - 131
  • [8] Automated Optic Disc Removal in Fundus Images using Iterative Heuristics and Morphological Operations
    Hassan, H. A.
    Tahir, N. M.
    Yassin, I.
    Zabidi, A.
    Yahaya, C. H. C.
    Shafie, S. M.
    2013 IEEE CONFERENCE ON SYSTEMS, PROCESS & CONTROL (ICSPC), 2013, : 230 - 233
  • [9] Noise removal for Multi-echo MR images using Global Enhancement
    Hong, Seongwook
    Cui, Xuenan
    Li, Shengzhe
    June, Naw Chit Too
    Kwack, Kyu-sung
    Kim, Hakil
    IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2010), 2010, : 3616 - 3621
  • [10] Salt and pepper noise removal in binary images using image block prior probabilities
    Pyatykh, Stanislav
    Hesser, Juergen
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2014, 25 (05) : 748 - 754