development of an leaf tracking algorithm on corn plants
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Plant Phenomics leaf trackingTRANSCRIPT
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life science research
high-throughput screening
plant functional genomics
ecotoxicology
high-content screening
cell analysis
colony counting
drug discovery
quality control
Development of an leaf tracking algorithm on corn plants
Speaker: Stefan Schwartz
challanges and aim
idea and algorithm
implementation
results
discussion
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
idea and algorithm
implementation
results
discussion
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
idea and algorithm
implementation
results
discussion
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
idea and algorithm
implementation
results
discussion
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
idea and algorithm
implementation
results
discussion
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
idea and algorithm
implementation
results
discussion
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
challanges and aim
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 9
LemnaTec develops hardware- and software solutions for automated high throuput phenotyping
main aim is the digital quantification of plant features in
and beyond human perception
software development includes
hardware control
database management
image processing
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 10
challanges and aim
challanges and aim
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 11
many information on the outer shape of a plant are available
would it possible to identify the structure of a plant?
how could leaves be counted?
challanges and aim
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 12
to keep track on single leaves the inner structure of the plant needs to be identified and the plant has to be segmented
leaf 1
leaf 2
leaf 3
leaf 4
leaf 5 leaf 6
idea and algorithm
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 14
skeletonization algorithms reduce surfaces to single lines
skeletonization is already used to identify objects (e.g. fingerprinting)
graph theory provides a big amount of algorithms for path analysis
Image Skeleton Graph
Segmented Plant
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 15
the idea of the algorithm can therefore be divided into 5 steps:
create graph
simplify graph
interpret graph I (stem)
interpret graph II (leaves)
vectorise and tabulate data
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 16
skeletons contain all points that have at least two border points with the same distance to the point itself
the skeleton is divided into joints and bones
the outer shape of the original object is still avaiable
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 17
a graph is used to show connections between certain points
it contains edges and vertices
its structure is saved in a matrix
multiple efficient path tracking algorithms are described for graphs
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 18
the skeleton will be transformed into a graph
bones become edges
joints become vertices
J2
J1
B1
B2 B3
B4
B5
B6
V1
V2
V5
V7
V4
V6
V3
E1
E2 E3
E4
E5
E6
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 19
the sekelton and therefore the created graph can contain artifacts
these artifacts can massivly influence later analysis steps
gap
false edge
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 20
the mean edge length is calculated 𝑙𝑒𝑖 ≔ 𝑙𝑒𝑛𝑔𝑡 𝑜𝑓 𝑒𝑑𝑔𝑒 𝑒𝑖
𝑙 = 1
|𝔼| 𝑙𝑒𝑖
|𝔼|
𝑖 = 0
for each vertex with just one outgoing edge:
gaps will be filled if: 𝑣𝑖𝑣𝑗 ≤ 𝜚 ∙ 𝑙
edges will be deleted if: 𝑙𝑒𝑘 ≤ 𝑙 ∙ 𝜑
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 21
the stem is a straight path in the center of the plant
the initial and end direction of each edge is calculated
𝛾𝑎 = ∢ 𝑒 , 𝑎 𝛾𝑏 = ∢ 𝑒 , 𝑏 𝑚𝑖𝑡 0 ≤ 𝛾𝑎 , 𝛾𝑏 ≤ 𝜋
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 22
the Dijkstra-Algorithm calculates a path between an initial and an end vertex with the lowest costs
the initial vertex kann be manually configured
the costs of an edge can be determined with the defined directions
stem ends in the highest branch
𝑪𝒐𝒔𝒕𝑺 𝒆𝒊 = 𝜸𝒂 −𝝅
𝟐+ 𝜸𝒃 −
𝝅
𝟐
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 23
leaves begin on a leaf tip and grow on an even path to the stem
the costs of each edge were calculated by using the angle of the intersection to the next leaf
𝐶𝑜𝑠𝑡𝐿 𝑒𝑖 , 𝑒𝑗 = 𝜋 − (𝛾𝑎,𝑒𝑗 + 𝛾𝑏,𝑒𝑖)
idea and algorithm
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 24
complex structure of leaves is represented by using three characteristic points
each leaf is numbered by the Point S
α = ∢ 𝑒 , 𝑆𝑇 β = ∢ 𝑆𝑇 , 𝐸𝑇 γ = ∢ 𝑒 , 𝐸𝑇 𝑚𝑖𝑡 0 ≤ α, β, γ ≤ 𝜋
implementation
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
implementation
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 26
integrated in existing software (LemnaGrid)
graphical User Interface for development of image processing chains
results
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
results
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 28
results
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 29
results
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 30
results
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 31
discussion
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
discussion
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 33
leaves and stem have been identified
analysis without mistakes can not be guaranted
quality criteria improves results
algorithm was tested on a big corn database
using the quality criteria decreased the number of results by 7%
future prospects
Overview
Date: 2/15/2011 Speaker: Stefan Schwartz
Future prospects
Date: 2/15/2011 Speaker: Stefan Schwartz Slide 35
algorithm could compare two images
creating 3D models to avoid length changes due to rotation effects
devolving the algorithm to other plants
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