SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

Graham, D.G., Reid, I. and Rice, S.P. (2005) Automated Sizing of Coarse Grained Sediments: Image Processing Procedures. Mathematical Geology, 37, 1-28.
https://doi.org/10.1007/s11004-005-8745-x

has been cited by the following article:

  • TITLE: Gravel Image Auto-Segmentation Based on an Improved Normalized Cuts Algorithm

    AUTHORS: Chao Wang, Xiangliang Lin, Changsheng Chen

    KEYWORDS: Normalized Cuts, Gravel Image, Auto-Segmentation

    JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.7 No.3, March 25, 2019

    ABSTRACT: The study of the grain-size distribution of gravels is always an important and challenging issue in stratigraphy and morphology, especially in the field of automated measurement. It largely reduces many manual processes and time consumption. Precise segmentation method plays a very important role in it. In this study, a digital image method using an improved normalized cuts algorithm is proposed for auto-segmentation of gravel image. It added grain-size estimation, and used the feature vector based on color. It has made great improvements in many respects, especially in accuracy of edge segmentation and automation. Compared with manual measurement methods and other image processing methods, the method studied in this paper is an efficient method for precisely segmenting gravel images.