Paper Info
Title
Leaf Segmentation And Parallel Phenotyping For The Analysis Of Gene Networks In Plants
Abstract
Over the last 4 years phenotyping is becoming more and more automated, decreasing a lot of manual labour. Features, which uniquely define the plant, can be extracted automatically from images. As a lot of plant data has to be processed in order to extract the features, fast processing of these features is a challenge. Therefore in this paper, a new method for automatic segmentation of individual leaves from plants with a circular arrangement of leaves (rosettes) is proposed, together with an algorithm to extract the line of symmetry of the leaf. Furthermore, in order to achieve fast processing for phenotyping plants, four feature extraction methods are parallelised in order to run on the CPU and GPU. Our evaluation results show that by parallelizing the feature extraction methods, it is possible to calculate the image moments, area, histogram and sum of intensities 5 to 45 times faster than single threaded implementations.
Year
Venue
Keywords
2013
2013 PROCEEDINGS OF THE 21ST EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)
segmentation, parallelisation, phenotyping, OpenCl, image processing
Field
DocType
Citations 
Computer vision,Histogram,Central processing unit,Scale-space segmentation,Segmentation,Computer science,Image processing,Feature extraction,Artificial intelligence,Gene regulatory network,Image moment
Conference
1
PageRank 
References 
Authors
0.35
0
8
Name
Order
Citations
PageRank
Olivier Janssens1169.32
Jonas De Vylder2147.62
Jan Aelterman38011.46
Steven Verstockt45513.58
Wilfried Philips51476124.85
Dominique Van Der Straeten6102.05
Sofie Van Hoecke711326.27
Rik Van de Walle82040238.28