A new clustering algorithm for scanning electron microscope images

Amr Yousef; Prakash Duraisamy; Mohammad Karim

doi:10.1117/12.2224251

20 April 2016 A new clustering algorithm for scanning electron microscope images

Amr Yousef, Prakash Duraisamy, Mohammad Karim

Proceedings Volume 9845, Optical Pattern Recognition XXVII; 984509 (2016) https://doi.org/10.1117/12.2224251
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

A scanning electron microscope (SEM) is a type of electron microscope that produces images of a sample by scanning it with a focused beam of electrons. The electrons interact with the sample atoms, producing various signals that are collected by detectors. The gathered signals contain information about the sample’s surface topography and composition. The electron beam is generally scanned in a raster scan pattern, and the beam’s position is combined with the detected signal to produce an image. The most common configuration for an SEM produces a single value per pixel, with the results usually rendered as grayscale images. The captured images may be produced with insufficient brightness, anomalous contrast, jagged edges, and poor quality due to low signal-to-noise ratio, grained topography and poor surface details. The segmentation of the SEM images is a tackling problems in the presence of the previously mentioned distortions. In this paper, we are stressing on the clustering of these type of images. In that sense, we evaluate the performance of the well-known unsupervised clustering and classification techniques such as connectivity based clustering (hierarchical clustering), centroid-based clustering, distribution-based clustering and density-based clustering. Furthermore, we propose a new spatial fuzzy clustering technique that works efficiently on this type of images and compare its results against these regular techniques in terms of clustering validation metrics.

Citation Download Citation

Amr Yousef, Prakash Duraisamy, and Mohammad Karim "A new clustering algorithm for scanning electron microscope images", Proc. SPIE 9845, Optical Pattern Recognition XXVII, 984509 (20 April 2016); https://doi.org/10.1117/12.2224251

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available