Detail publikace

Image analysis applied to quartz grain microtextural provenance studies

ŘÍHA, K. KŘUPKA, A. COSTA, P.

Originální název

Image analysis applied to quartz grain microtextural provenance studies

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Every quartz grain surface is sculptured during time by many different processes. During the life of a grain, sediment transport, physical and chemical processes imprint specific microtextural features on their surface. State-of-the-art methods for analysis of the surface of quartz particles in Scanning Electron Microscope images are performed non-automatically by experts and essentially are dependent on operator proficiency. Here, we propose digital image processing-based method for automated microtextural analysis of grain's surface with the goal to classify the grain into specific classes corresponding to its genesis (last provenance cycle). The method is based on original classification scheme which extracts the textural features from the digital images of single grains in training database and creates Texton Dictionary for establishing the prototype of specific texture set characterizing given genesis class. The created Texton Dictionary then can be used for classification of a grain with unknown genesis with very good performances when tested on databases of grains with known origins.

Klíčová slova

MicrotexturesImage analysisSedimentologyQuartz grainsTexton dictionary

Autoři

ŘÍHA, K.; KŘUPKA, A.; COSTA, P.

Vydáno

9. 4. 2019

ISSN

0098-3004

Periodikum

COMPUTERS & GEOSCIENCES

Číslo

125

Stát

Spojené království Velké Británie a Severního Irska

Strany od

98

Strany do

108

Strany počet

11

URL

https://www.sciencedirect.com/science/article/pii/S0098300418305752

BibTex

@article{BUT157481,
  author="Kamil {Říha} and Aleš {Křupka} and Pedro J.M. {Costa}",
  title="Image analysis applied to quartz grain microtextural provenance studies",
  journal="COMPUTERS & GEOSCIENCES",
  year="2019",
  number="125",
  pages="98--108",
  doi="10.1016/j.cageo.2019.01.007",
  issn="0098-3004",
  url="https://www.sciencedirect.com/science/article/pii/S0098300418305752"
}