Authors:
Andrew French
1
;
Malcolm Bennett
1
;
Caroline Howells
1
;
Dhaval Patel
2
and
Tony Pridmore
1
Affiliations:
1
Centre for Plant Integrative Biology, University of Nottingham, United Kingdom
;
2
Plant Sciences, School of Biosciences, University of Nottingham, United Kingdom
Keyword(s):
Particle filter, image analysis, quantification, bioinformatics.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
This paper introduces a new methodology to aid the tracing and measurement of lines in digital images. The techniques in this paper have specifically been applied to the labour intensive process of measuring roots in digital images. Current manual methods can be slow and error prone, and so we propose a semi-automatic way to trace the root image and measure the corresponding length in the image plane. This is achieved using a particle filter tracker, normally applied to object tracking though time, to trace along a root in an image. The samples the particle filter generates are used to build a probabilistic graph across the root location in the image, and this is traversed to produce a final estimate of length. The software is compared to real-world and artificial length data. Extensions of the algorithm are noted, including the automatic detection of the end of the root, and the detection of multiple growth modes using a mixed state particle filter.