Automatic characterization of nanofiber assemblies by image texture analysis

Chemometrics and Intelligent Laboratory Systems

Volumn 103, Issue 1, 2010, Pages 66-75

  Facco, Pierantonio ^a   Tomba, Emanuele ^a   Roso, Martina ^a   Modesti, Michele ^a   Bezzo, Fabrizio ^a   Barolo, Massimiliano ^a  

^a UNIVERSITY OF PADOVA   (Italy)

Author keywords

Electrospinning; Image texture analysis; Multi resolution methods; Multivariate statistical methods; Nanofibers; Nanomaterials; Quality monitoring; Statistical process control

Indexed keywords

NANOFIBER;

ARTICLE; AUTOMATION; DIGITAL IMAGING; ELECTROSPINNING; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE TEXTURE ANALYSIS; NANOFABRICATION; NANOPORE; NANOTECHNOLOGY; PERFORMANCE MEASUREMENT SYSTEM; PRIORITY JOURNAL; PROCESS DESIGN; QUALITATIVE RESEARCH; SCANNING ELECTRON MICROSCOPY; SPECTRAL SENSITIVITY; SYSTEM ANALYSIS;

EID: 77954658985     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2010.05.018     Document Type: Article

References (31)

1. Gopal R., Kaur S., Yang Feng C., Chan C., Ramakrishna S., Tabe S., Matsuura T. Electrospun nanofibrous polysulfone membranes as pre-filters: particulate removal. J. Membr. Sci. 2007, 289:210-219.
2. Kim J.-S., Reneker D.H. Mechanical properties of composites using ultrafine electrospun fibers. Polym. Compos. 1999, 20:124-131.
3. Gibson P., Schreuder-Gibson H., Rivin D. Transport properties of porous membranes based on electrospun nanofibers. Colloids Surf. 2001, 187-188:469-481.
4. Min B.M., Lee G., Kim S.H., Nam Y.S., Lee T.S., Park W.H. Electrospinning of silk fibroin nanofibers and its effect on the adhesion and spreading of normal human keratinocytes and fibroblasts in vitro. Biomaterials 2004, 25:1289-1297.
5. Roso M., Sundarrajan S., Pliszka D., Ramakrishna S., Modesti M. Multifunctional membranes based on spinning technologies: the sinergy of nanofibers and nanoparticles. Nanotechnology 2008, 19:1-6.
6. Agarwal S., Wendorff J.H., Greiner A. Use of electrospinning technique for biomedical applications. Polymer 2008, 49:5603-5621.
7. Kenawy E.-R., Abdel-Hay F.I., El-Newehy M.H., Wnek G.E. Processing of polymer nanofibers through electrospinning as drug delivery systems. Mater. Chem. Phys. 2009, 113:296-302.
8. Gomes D.S., da Silva A.N.R., Morimoto N.I., Mendes L.T.F., Furlan R., Ramos I. Characterization of an electrospinning process using different PAN/DMF concentrations. Polím. Ciênc. Tecnol. 2007, 17:206-211.
9. Tomba E., Facco P., Roso M., Modesti M., Bezzo F., Barolo M. Artificial vision system for the automatic measurement of inter-fiber pore characteristics and fiber diameter distribution in nanofiber assemblies. Ind. Eng. Chem. Res. 2010, 49:2957-2968.
10. Gonzales R.C., Woods R.E. Digital Image Processing 2002, Prentice-Hall, Inc., Upper Saddle River, New Jersey (U.S.A.).
11. Geladi P., Grahn H. Multivariate Image Analysis 1996, John Wiley & Sons, Inc., New York (U.S.A.).
12. Bharati M.H., Liu J.J., MacGregor J.F. Image texture analysis: methods and comparisons. Chemom. Intell. Lab. Syst. 2004, 72:57-71.
13. Prats-Montalbàn J.M., Ferrer A. Integration of colour and textural information in multivariate image analysis: defect detection and classification issues. J. Chemom. 2007, 21:10-23.
14. Borah S., Hines E.L., Bhuyan M. Wavelet transform based image texture analysis for size estimation applied to the sorting of tea granules. J. Food Eng. 2007, 79:629-639.
15. Tessier J., Duchesne C., Gauthier C., Dufour G. Estimation of alumina content of anode cover materials using multivariate image analysis techniques. Chem. Eng. Sci. 2008, 63:1370-1380.
16. Kucheryavski S., Belyaev I., Fominykh S. Estimation of age in forensic medicine using multivariate approach to image analysis. Chemom. Intell. Lab. Syst. 2009, 97:39-45.
17. Andrady A.L. Science and Technology of Polymer Nanofibers 2008, John Wiley & Sons Inc., New York (U.S.A.).
18. Rutledge G.C., Fridrikh S.V. Formation of fibers by electrospinning. Advanced drug. delivery reviews 2007, 59:1384-1391.
19. Johnston P.R. Fluid Sterilization by Filtration 2004, CRC Press LLC, Boca Raton, FL (U.S.A.). Third Edition.
20. Mallat S.G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 1989, 11:674-693.
21. Addison P.S. The Illustrated Wavelet Transform Handbook 2002, Taylor & Francis, New York (U.S.A.).
22. Bharati M.H., MacGregor J.F. Multivariate image analysis for real-time process monitoring and control. Ind. Eng. Chem. Res. 1998, 37:4715-4724.
23. Jackson J.E. A User's Guide to Principal Components 1991, John Wiley & Sons Inc., New York (U.S.A.).
24. Geladi P., Kowalski B. Partial least-squares regression: a tutorial. Anal. Chim. Acta 1986, 185:1-17.
25. Nomikos P., MacGregor J.F. Monitoring batch processes using multiway principal component analysis. AIChE J. 1994, 40:1361-1375.
26. Green A.A., Berman M., Switzer P., Craig M.D. A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Trans. Geosci. Remote Sens. 1988, 26:65-74.
27. Larsen R. Decomposition using maximum autocorrelation factors. J. Chemom. 2002, 16:427-435.
28. Haralick R.M., Shanmugan K., Dinstein I. Textural features for image classification. IEEE Trans. Syst. Man Cybern. 1973, 3:610-621.
29. Liu J.J., MacGregor J.F., Duchesne C., Bartolacci G. Flotation froth monitoring using multiresolutional multivariate image analysis. Min. Eng. 2005, 18:65-76.
30. Liu J.J., MacGregor J.F. On the extraction of spectral and spatial information from images. Chemom. Intell. Lab. Syst. 2007, 85:119-130.
31. Wise B.M., Gallagher N.B. The process chemometrics approach to process monitoring and fault detection. J. Process Control 1996, 6:329-348.