Efficient affine-invariant fourier descriptors for identification of marine plankton

Zonghua Liu, John Watson, Alastair Allen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A study of population and distribution of plankton in the sea can be a good indicator of the health of the marine environment. Many digital images of marine plankton have been recorded. Image extraction and plankton identification can aid research of oceanic plankton. In this paper, we present a method to compute affine-invariant Fourier Descriptors (FDs) for marine plankton image retrieval. This method computes FDs of a shape boundary through the quasi-continuous Fourier transform. The experimental results show that the proposed FDs capture more information of the shape boundary than the the same number of traditional discrete FDs. Before calculation of FDs, each plankton image is pre-processed and the plankton shape is compacted into the boundary polygon. We have developed a set of approaches to quickly extract the exact and compact boundary polygon of an object, including methods of edge detection, boundary tracing, coordinate compensation of the boundary points and break-point detection. An affine-invariant curve normalization method then is adopted to reduce the geometrical deformations or distortions from the polygonal boundary curves possibly caused by changes of the camera angle. The experimental implementation shows that this curve normalization method is robust and can successfully eliminate transformations of translation, scaling, non-uniform scaling and shearing from two affine-transform-related curves. Lastly, the ability of the proposed FDs to identify plankton images with deformations is tested on an artificial image dataset. The experiment shows that the proposed FDs have better performance than the traditional FDs in terms of retrieval efficiency.

Original languageEnglish
Title of host publicationOCEANS 2017 - Aberdeen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-9
Number of pages9
Volume2017-October
ISBN (Electronic)9781509052783
DOIs
Publication statusPublished - 25 Oct 2017
EventOCEANS 2017 - Aberdeen - Aberdeen, United Kingdom
Duration: 19 Jun 201722 Jun 2017

Conference

ConferenceOCEANS 2017 - Aberdeen
CountryUnited Kingdom
CityAberdeen
Period19/06/1722/06/17

Keywords

  • affine-invariant curve normalization
  • Fourier descriptors
  • marine plankton
  • pattern identification

Fingerprint Dive into the research topics of 'Efficient affine-invariant fourier descriptors for identification of marine plankton'. Together they form a unique fingerprint.

  • Cite this

    Liu, Z., Watson, J., & Allen, A. (2017). Efficient affine-invariant fourier descriptors for identification of marine plankton. In OCEANS 2017 - Aberdeen (Vol. 2017-October, pp. 1-9). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/OCEANSE.2017.8084832