scholarly journals Evaluation of scanning electron microscopy images of a model dressing using image feature extraction techniques and principal component analysis

Scanning ◽  
2006 ◽  
Vol 21 (5) ◽  
pp. 316-325 ◽  
Author(s):  
Bjørg Egelandsdal ◽  
Kirsti F. Christiansen ◽  
Vibeke Høst ◽  
Frank Lundby ◽  
Jens Petter Wold ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Principal Component Analysis ◽  
Feature Extraction ◽  
Principal Component ◽  
Image Feature ◽  
Extraction Techniques ◽  
Image Feature Extraction ◽  
Microscopy Images ◽  
Scanning Electron

Scanning Electron Microscopy and Geometric Contour Morphometry for Identifying Eggs of Three Amazonian Species of Mansonia (Diptera: Culicidae)

2019 ◽  
Vol 57 (3) ◽  
pp. 745-754
Author(s):  
Francisco Augusto da Silva Ferreira ◽  
Rejane de Castro Simões ◽  
Ruth Leila Ferreira-Keppler ◽  
Jeronimo Alencar ◽  
Vera Margarete Scarpassa ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Accuracy Rate ◽  
Morphometric Characters ◽  
Geometric Morphometry ◽  
Neotropical Species ◽  
Egg Morphology ◽  
Scanning Electron

Abstract The eggs of three Amazonian species of the genus Mansonia (Diptera: Culicidae) were analyzed using morphological and morphometric characters. Eggs of Mansonia humeralis Dyar & Knab, 1916 were morphologically different from those of Mansonia titillans (Walker, 1848) and Mansonia amazonensis (Theobald, 1901), which were more similar to each other according to linear and geometric morphometry. A principal component analysis generated from elliptic Fourier contour data (PC1—92.6% and PC2—2.61%) indicated that Ma. amazonensis and Ma. titillans are more similar to each other than either is to Ma. humeralis. Discriminant multivariate analysis was highly accurate with only four classification errors and a 90% accuracy rate. The results indicate that the three Amazonian species can be precisely distinguished in the egg stage and that geometric morphometry based on elliptic Fourier contours is a promising method for distinguishing eggs of species of Mansonia. An identification key based on egg morphology is provided to distinguish the four Neotropical species.

scholarly journals Comparative morphology and anatomy of seeds of some Aethionema W.T. Aiton (Brassicaceae) taxa from Turkey

2019 ◽  
Vol 26 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Mehmet Cengiz Karaismailoğlu
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Comparative Morphology ◽  
Seed Morphology ◽  
Anatomical Features ◽  
Major Significance ◽  
Surface Patterns ◽  
Scanning Electron

Seed morphology and anatomy are taxonomically significant in Brassicaceae. The seed structures of Aethionema from Turkey, which include 12 taxa (Aethionema syriacum, A. froedinii, A. arabicum, A. eunomioides, A. fimbriatum, A. speciosum subsp. speciosum, A. speciosum subsp. compactum, A. saxatile, A. oppositifolium, A. iberideum, A. armenum, A. grandiflorum) were studied for knowing seed morphological and anatomical features with one-way analysis of variance, cluster analysis and principal component analysis. Seed size, shape and color were examined with stereomicroscopy.The surface patterns of seed were observed using Scanning Electron Microscopy (SEM). In addition, structure, and thicknesses of testa and endosperm were investigated anatomically. Thickness of testa and endosperm were of major significance to illustrate interspecific relations among the examined taxa.

scholarly journals Clay-Based Brick Porosity Estimation Using Image Processing Techniques

2019 ◽  
Vol 29 (1) ◽  
pp. 1226-1234
Author(s):  
Safa Jida ◽  
Hassan Ouallal ◽  
Brahim Aksasse ◽  
Mohammed Ouanan ◽  
Mohamed El Amraoui ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Computer Vision ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Porosity Estimation ◽  
Microscopy Images ◽  
Scanning Electron

Abstract This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation.

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