Evolving Complete L-Systems: Using Genetic Algorithms for the Generation of Realistic Plants

Fitch, Benjamin G.; Parslow, Patrick; Lundqvist, Karsten

doi:10.1007/978-3-319-90418-4_2

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…L-systems typically evolve from a mathematical theory of plant and cellular growth [12]. They are based upon the Backus-Naur production rules and allow for extensive application of plant-based synthetic imagery [13], [14], [15]. L-systems are particularly useful in the ability to recognize and measure real wheat plants.…”

Section: Background and Literaturementioning

confidence: 99%

Improved image recognition via Synthetic Plants using 3D Modelling with Stochastic Variations

Napier,

Cook,

Armstrong

et al. 2023

BIO Web Conf.

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This research extends previous plant modelling using L-systems by means of a novel arrangement comprising synthetic plants and a refined global wheat dataset in combination with a synthetic inference application. The study demonstrates an application with direct recognition of real plant stereotypes, and augmentation via a plant-wide stochastic growth variation structure. The study showed that the automatic annotation and counting of wheat heads using the Global Wheat dataset images provides a time and cost saving over traditional manual approaches and neural networks. This study introduces a novel synthetic inference application using a plant-wide stochastic variation system, resulting in improved structural dataset hierarchy. The research demonstrates a significantly improved L-system that can more effectively and more accurately define and distinguish wheat crop characteristics.

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Section: Background and Literaturementioning

confidence: 99%

Improved image recognition via Synthetic Plants using 3D Modelling with Stochastic Variations

Napier,

Cook,

Armstrong

et al. 2023

BIO Web Conf.

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“…• Spatial Algorithms (SA), e.g., Tiling and layering, Grid subdivision, Fractals, Voronoi Diagrams Aristid Lindenmayer [Lin68] created Lindenmayer systems (L-systems) to model multi-cellular organisms, but their versatility proved suitable for modelling plants [Fit18] with three-like structures [Cio09]. L-systems are a formal grammar that produces strings that get rewritten over time, in parallel.…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of the underwater environment in the procedural generation of marine alga Asparagopsis Armata

Rodrigues¹,

Sousa²,

Rodrigues³

et al. 2022

CSRN

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Content generation is a heavy task in virtual worlds design. Procedural content generation techniques aim to agile this process by automating the 3D modelling with some degree of parametrisation. The novelty of this work is the procedural generation of the marine alga (Asparagopsis armata), taking into consideration the underwater environmental factors. The depth and the occlusion were the two parameters in this study to simulate how the alga growth is influenced by the environment where the alga grows. Starting by building a prototype to explore different L-systems categories to model the alga, the stochastic L-systems with parametric features were selected to generate different alga plasticities. Qualitative methods were used to evaluate the designed grammar and alga’s animation results by comparing videos and images of the Asparagopsis armata with the computer-generated versions.

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Evolving L-Systems in a Competitive Environment

Talle

Kosinka

2020

Lecture Notes in Computer Science

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Evolving Complete L-Systems: Using Genetic Algorithms for the Generation of Realistic Plants

Cited by 4 publications

References 9 publications

Improved image recognition via Synthetic Plants using 3D Modelling with Stochastic Variations

Improved image recognition via Synthetic Plants using 3D Modelling with Stochastic Variations

Influence of the underwater environment in the procedural generation of marine alga Asparagopsis Armata

Evolving L-Systems in a Competitive Environment

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