In this article, we present an approach for the automated extraction of quantitative information about trichome patterning on leaves of Arabidopsis thaliana. Time series of growing rosette leaves (4D confocal datasets...
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ISBN:
(纸本)9781424439317
In this article, we present an approach for the automated extraction of quantitative information about trichome patterning on leaves of Arabidopsis thaliana. Time series of growing rosette leaves (4D confocal datasets, 3D + time) are used for this work. At first, significant anatomical structures, i.e. leaf surface and midplane are extracted robustly. Using the extracted anatomical structures, a biological reference coordinate system is registered to the leaves. The performed registration allows to determine intra- as well as inter-series spatiotemporal correspondences. Trichomes are localized by first detecting candidates using Hough transform. Then, local 3D invariants are extracted and the candidates are validated using a Support Vector Machine (SVM).
We present a novel method for the fast computation of rotation invariant ¿local binary patterns¿ (LBP) on 3D volume data. Unlike a previous publication on 3D LBP, this new approach is not limited to ¿un...
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We present a novel method for the fast computation of rotation invariant ¿local binary patterns¿ (LBP) on 3D volume data. Unlike a previous publication on 3D LBP, this new approach is not limited to ¿uniform patterns¿, providing a real 3D extension of the standard and rotation invariant LBP. We evaluate our methods in the context of 3D texture analysis of biological data.
We propose a classification method based on a decision tree whose nodes consist of linear support vector machines (SVMs). Each node defines a decision hyperplane that classifies part of the feature space. For large cl...
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We propose a classification method based on a decision tree whose nodes consist of linear support vector machines (SVMs). Each node defines a decision hyperplane that classifies part of the feature space. For large classification problems (with many support vectors (SVs)) it has the advantage that the classification time does not depend on the number of SVs. Here, the classification of a new sample can be calculated by the dot product with the orthogonal vector of each hyperplane. The number of nodes in the tree has shown to be much smaller than the number of SVs in a non-linear SVM, thus, a significant speedup in classification time can be achieved. For non-linear separable problems, the trivial solution (zero vector) of a linear SVM is analyzed and a new formulation of the optimization problem is given to avoid it
An algorithm to group edge points into digital line segments with Hough transformation is described. The edge points are mapped onto the parameter domain discretized at specific intervals, on which peaks appear to rep...
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ISBN:
(纸本)0769507506
An algorithm to group edge points into digital line segments with Hough transformation is described. The edge points are mapped onto the parameter domain discretized at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region to which the edge points are supposed to be mapped is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation for detecting peaks one by one in the parameter domain is implemented, and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both the generated edges disturbed by different noise levels and real images taken from an indoor environment.
作者：
Moga, Alina N.Albert-Ludwigs-Universität
Institut für Informatik Chair for Pattern Recognition and Image Processing Universitätsgelände Flugplatz Freiburg i.BrD-79085 Germany
A parallel extension for the watershed segmentation is presented in this paper. By following regional minima, i.e. the seeds around which regions are grown, in images of lower resolution, a region merging criterion in...
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