Open AccessAnalysis of Image Processing Using Morphological Erosion and Dilation
Author(s) -
Khairul Anuar Mat Said,
Asral Bahari Jambek
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2071/1/012033
Subject(s) - structuring element , dilation (metric space) , structuring , morphological gradient , binary image , image processing , computer vision , mathematical morphology , artificial intelligence , computer science , top hat transform , digital image processing , erosion , digital image , image quality , image (mathematics) , pattern recognition (psychology) , mathematics , geology , paleontology , finance , combinatorics , economics
Digital image processing is important for image information extraction. One of the image processing methods is morphological image processing. This technique uses erosion and dilation operations to enhance and improve the image quality by shrinking and enlarging the image foreground. However, morphological image processing performance depends on the characteristics of structuring elements and their foreground image that need to be extracted. This paper studies how the structuring elements affect the performance of morphological erosion and dilation on binary images. The experimental result shows that choosing the right structuring element for morphological erosion and dilation can significantly influence the foreground and background structure of the output image.