Diatom identification including life cycle stages through morphological and texture descriptors

• Published in: PeerJ (San Francisco, CA) CA), 2019-04, Vol.7, p.e6770-e6770, Article e6770
• Main Authors: Sánchez, Carlos, Cristóbal, Gabriel, Bueno, Gloria
• Format: Article
• Language: English
• Subjects: Algae; Analysis; Artificial intelligence; Asymmetry; Automated identification; Automation; Biogeography; Bioinformatics; Classification; Clustering; Criminal investigation; Decorative arts; Environmental studies; Forensic science; Forensic sciences; Freshwater Biology; Identification; Life cycles; Marine Biology; Methods; Microbiology; Morphology; Neural networks; Principal components analysis; Quality control; Taxonomy; Texture; Water quality
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.6770

Diatoms are unicellular algae present almost wherever there is water. Diatom identification has many applications in different fields of study, such as ecology, forensic science, etc. In environmental studies, algae can be used as a natural water quality indicator. The diatom life cycle consists of the set of stages that pass through the successive generations of each species from the initial to the senescent cells. Life cycle modeling is a complex process since in general the distribution of the parameter vectors that represent the variations that occur in this process is non-linear and of high dimensionality. In this paper, we propose to characterize the diatom life cycle by the main features that change during the algae life cycle, mainly the contour shape and the texture. Elliptical Fourier Descriptors (EFD) are used to describe the diatom contour while phase congruency and Gabor filters describe the inner ornamentation of the algae. The proposed method has been tested with a small algae dataset (eight different classes and more than 50 samples per type) using supervised and non-supervised classification techniques obtaining accuracy results up to 99% and 98% respectively.