Coal micrograph segmentation based On visual clustering

Author

Wang, Peizhen ; Chen, Shanshan ; Zhang, Dailin

Author_Institution

Sch. of Electr. Eng. & Inf., Anhui Univ. of Technol., Ma´´anshan, China

fYear

2011

fDate

21-25 June 2011

Firstpage

683

Lastpage

687

Abstract

In order to distinguish different components of macerals from coal micrograph, a visual clustering algorithm that is inspired from visual psychology is proposed. It mimics the mechanism of the human visual system. There are two procedures: the hierarchical feature extraction mechanism dominated by receptive field functions and the feature integration principle characterized by Gestalt law in psychology. Experimental results show that the proposed algorithm performs well for the coal micrograph segmentation compared with other methods.

Keywords

coal; feature extraction; graph theory; image segmentation; pattern clustering; Gestalt law; coal micrograph segmentation; feature integration principle; hierarchical feature extraction mechanism; human visual system; receptive field function; visual clustering algorithm; visual psychology; Clustering algorithms; Coal; Feature extraction; Image segmentation; Neurons; Psychology; Visualization; Gestalt Laws; Hierarchical Clustering; Receptive Field Function; Visual Clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2011 9th World Congress on

Conference_Location

Taipei

Print_ISBN

978-1-61284-698-9

Type

conf

DOI

10.1109/WCICA.2011.5970602

Filename

5970602