NDLI: Texture Classification in Microstructure Images of Advanced Materials

Content Provider	IEEE Xplore Digital Library
Author	Hsiao-Chiang Chuang Comer, M.L. Simmons, J.P.
Copyright Year	2008
Description	Author affiliation: Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN (Hsiao-Chiang Chuang; Comer, M.L.)
Abstract	In this paper we discuss texture classification of microstructural images used in the development of advanced materials. Different materials or different phases of a material in a sample lead to different textures in images of that sample. We investigate the application of the expectation-maximization/ maximization of the posterior marginal (EM/MPM) algorithm proposed in [1] for automated texture-based segmentation of these microstructure images. We propose a new method to initialize the parameters used for the observed image under a Gaussian model. In addition, we examine the use of 8-nearest- neighborhood system for segmentation to locate objects edges more precisely. The experimental results demonstrate the adaptability of the EM/MPM algorithm with appropriate choices of model parameters and neighborhood system. Furthermore, we demonstrate that the use of 8-nearest-neighborhood system can provide smoother segmentation in edges.
Starting Page	1
Ending Page	4
File Size	264646
Page Count	4
File Format	PDF
ISBN	9781424422968
DOI	10.1109/SSIAI.2008.4512270
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Microstructure
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

The role of the Textural Microstructure Cooccurrence Matrices in the classification of the abdominal tumors, based on ultrasound images

Microstructure Analysis of Petrographic Images Using Stochastic Texture Classification and Multiple Classifier Combinations

Polarimetric SAR Images Classification and Texture Features

Performance of texture descriptors in classification of medical images with outsiders in database

Microstructure preserving synthesis of biomedical images

Texture analysis and classification of SAR images of urban areas

Texture classification in remotely sensed images

Image resolution dependency of Local Texture Patterns in classification of color images

Novel approaches of texture feature extraction for image classification and recognition

Texture Classification in Microstructure Images of Advanced Materials

Similar Documents

The role of the Textural Microstructure Cooccurrence Matrices in the classification of the abdominal tumors, based on ultrasound images

Microstructure Analysis of Petrographic Images Using Stochastic Texture Classification and Multiple Classifier Combinations

Polarimetric SAR Images Classification and Texture Features

Performance of texture descriptors in classification of medical images with outsiders in database

Microstructure preserving synthesis of biomedical images

Texture analysis and classification of SAR images of urban areas

Texture classification in remotely sensed images

Image resolution dependency of Local Texture Patterns in classification of color images

Novel approaches of texture feature extraction for image classification and recognition

Texture Classification in Microstructure Images of Advanced Materials