A generic system for the classification of marble tiles using Gabor filters

2008 ◽  
Author(s):  
Ilktan Ar ◽  
Yusuf Sinan Akgul
Keyword(s):  
Gabor Filters ◽  
Generic System

The composition, generic placement and host-plant relationships of the joviana-group in the Parallelia generic complex (Lepidoptera : Noctuidae, Catocalinae)

2003 ◽  
Vol 17 (1) ◽  
pp. 111 ◽  
Author(s):  
Jeremy D. Holloway ◽  
Scott E. Miller
Keyword(s):  
New Species ◽  
Host Plant ◽  
Significant Preference ◽  
Larval Host ◽  
Two New Species ◽  
Lepidoptera Noctuidae ◽  
Generic System ◽  
Host Plant Relationships

The biosystematic position of the Parallelia generic complex is reviewed and a revised generic classification of its component taxa is presented. Bastilla Swinhoe (= Xiana Nye, syn. nov., Naxia Guenée, syn. nov.) is identified as the most appropriate genus for a large number of these taxa, including the joviana-group, which is reviewed in detail, with description of two new species, B. nielseni, sp. nov. and B. binatang, sp. nov. Parallelia prouti Hulstaert, syn. nov. and P. cuneifascia Hulstaert, syn. nov. are recognised as junior synonyms of Bastilla vitiensis Butler and two newly described Tahitian taxa are transferred into the joviana-group. Larval host records are examined in relation to this new generic system and significant preference for the Euphorbiaceae is noted for several groups: Bastilla, Buzara Walker (= Caranilla Moore, syn. nov., another segregate from Parallelia) and an Australian group within Grammodes Guenée.

Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

2017 ◽  
Author(s):  
Mehrdad Alvandipour ◽  
Scott E. Umbaugh ◽  
Deependra K. Mishra ◽  
Rohini Dahal ◽  
Norsang Lama ◽  
...  
Keyword(s):  
Image Analysis ◽  
Bone Cancer ◽  
Gabor Filters ◽  
Acl Rupture ◽  
Thermographic Image

scholarly journals Features Extraction for Pollen Recognition Using Gabor Filters

2018 ◽  
Vol 1 (2) ◽  
pp. 86
Author(s):  
Dimitar Nikolov Nikolov ◽  
Diana Dimitrova Tsankova
Keyword(s):  
Filter Bank ◽  
Recognition System ◽  
Gabor Filters ◽  
Features Extraction ◽  
Botanical Origin ◽  
Biologically Inspired ◽  
Microscope Images ◽  
European Pollen Database ◽  
Components Analysis

The aim of the article is to investigate the features extraction from microscope images of pollens for a classification of honey on the base of its botanical origin. A filter-bank of Gabor filters (as a biologically inspired recognition system) is used to obtain features, which are then post-processed using normalization, down-sampling (by bicubic interpolation), and principal components analysis (PCA). PCA is used for reducing the features size and a proper visualization of the features extraction results. Microscope images from the European pollen database, including pollen images of linden, acacia, lavender, rapeseed, and thistle, are used to illustrate capabilities of the proposed features extraction approach. The performance of the proposed algorithm is evaluated by simulations in MATLAB environment.

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