3D Invariants with High Robustness to Local Deformations for Automated Pollen Recognition

Ronneberger, Olaf; Wang, Qing; Burkhardt, Hans

doi:10.1007/978-3-540-74936-3_43

Cited by 21 publications

(13 citation statements)

References 10 publications

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“…Therefore they only determine a coarse bounding box and use all pixels therein for feature extraction, such that the features are disturbed by neighboring dust. The obtained recognition rate of 64.9% recognition rate at a precision of 30% for 8 different pollen taxa are significantly lower than the best segmentation based approaches of 84.3% recognition rate at a precision of 96.7% for 33 different taxa [1].…”

Section: Introductionmentioning

confidence: 61%

“…Furthermore, as mentioned above, correct segmentation is essential for pollen recognition. The good results of the pollen recognition [1] is also an indication of the success of the segmentation.…”

Section: Results Of Exact Segmentationmentioning

confidence: 90%

“…Our work with this dataset was first presented in [1], where the emphasis was on the derivation of invariant features. Here we will concentrate on the detection and segmentation of pollen grains.…”

Section: Introductionmentioning

confidence: 99%

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Fast and robust segmentation of spherical particles in volumetric data sets from brightfield microscopy

Ronneberger¹,

Wang²,

Burkhardt³

2008

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

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In this article we present an approach for a precise segmentation of spherical particles in transmitted light image stacks. A main goal was its fast operation and a high robustness to occlusions and agglomerations of the particles. The system is based on a voting procedure that finds the centers and radii of the particles and a subsequent precise segmentation with an active contour approach. To meet the demands of an online pollenmonitor for high speed and low memory consumption a multi-scale approach was applied. The proposed techniques successfully segmented the pollen grains in a vast amount of different air samples (about 2.7TB of raw data). The results on one of the most cluttered samples are presented in this paper.

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Section: Introductionmentioning

confidence: 61%

Section: Results Of Exact Segmentationmentioning

confidence: 90%

See 1 more Smart Citation

Fast and robust segmentation of spherical particles in volumetric data sets from brightfield microscopy

Ronneberger¹,

Wang²,

Burkhardt³

2008

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

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“…Differential-interference-contrast microscopy provides enhanced contrast of morphological features that have high spatial frequency (Inoué and Spring 1997) and has been adopted by palynologists working with pollen and spores in tropical settings that are characterized by many species separated by subtle morphological differences (e.g., Pardo-Trujillo et al 2003). Reflected-light (fluorescence) techniques, such as confocal and apotome microscopy, have been used to generate taxonomically significant data on the three-dimensional shape of entire pollen grains (Ronneberger et al 2002a(Ronneberger et al , 2002b(Ronneberger et al , 2007Punyasena et al 2012; figs. 3B, 4L) and structures within pollen grains (Hochuli and Feist-Burkhardt 2013), which can be difficult to acquire with transmitted-light techniques because of their relatively poor optical-sectioning capabilities (Sivaguru et al 2012).…”

Section: Seeing More: Microscopy In Palynologymentioning

confidence: 99%

On the Taxonomic Resolution of Pollen and Spore Records of Earth’s Vegetation

Mander

Punyasena

2014

International Journal of Plant Sciences

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Premise of research. Pollen and spores (sporomorphs) are a valuable record of plant life and have provided information on subjects ranging from the nature and timing of evolutionary events to the relationship between vegetation and climate. However, sporomorphs can be morphologically similar at the species, genus, or family level. Studies of extinct plant groups in pre-Quaternary time often include dispersed sporomorph taxa whose parent plant is known only to the class level. Consequently, sporomorph records of vegetation suffer from limited taxonomic resolution and typically record information about plant life at a taxonomic rank above species.Methodology. In this article, we review the causes of low taxonomic resolution, highlight examples where this has hampered the study of vegetation, and discuss the strategies researchers have developed to overcome the low taxonomic resolution of the sporomorph record. Based on this review, we offer our views on how greater taxonomic precision might be attained in future work.Pivotal results. Low taxonomic resolution results from a combination of several factors, including inadequate reference collections, the absence of sporomorphs in situ in fossilized reproductive structures, and damage following fossilization. A primary cause is the difficulty of accurately describing the very small morphological differences between species using descriptive terminology, which results in palynologists classifying sporomorphs conservatively at the genus or family level to ensure that classifications are reproducible between samples and between researchers.Conclusions. In our view, the most promising approach to the problem of low taxonomic resolution is a combination of high-resolution imaging and computational image analysis. In particular, we encourage palynologists to explore the utility of microscopy techniques that aim to recover morphological information from below the diffraction limit of light and to employ computational image analyses to consistently quantify small morphological differences between species.

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“…In 3D volumetric images, it is very common that similar objects presented in different orientations need to be recognized as the same class [10,19,22]. When objects have unknown poses, starting from rotation-invariant descriptions can make the following analysis easier since they are pose-independent.…”

Section: Introductionmentioning

confidence: 99%

3D Rotation-Invariant Description from Tensor Operation on Spherical HOG Field

Liu¹,

Skibbe²,

Schmidt³

et al. 2011

Procedings of the British Machine Vision Conference 2011

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Rotation-invariant descriptions are required in many 3D volumetric image analysis tasks. The histogram-of-oriented-gradient (HOG) is widely used in 2D images and proves to be a very robust local description. This paper concentrates on how to use the HOG feature in 3D volumetric images when rotation-invariance is concerned. This is challenging because of the complexity of 3D rotations. We present a decent solution based on the spherical harmonics theory which is an effective tool for analysing 3D rotations, together with the spherical tensor operations which explore high order tensor information in spherical coordinates. The design is quite general and could be used for different applications. It achieves high scores on Princeton Shape Benchmark and SHREC 2009 Generic Shape Benchmark, and also produces promising results when applying on biological microscopy images.

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3D Invariants with High Robustness to Local Deformations for Automated Pollen Recognition

Cited by 21 publications

References 10 publications

Fast and robust segmentation of spherical particles in volumetric data sets from brightfield microscopy

Fast and robust segmentation of spherical particles in volumetric data sets from brightfield microscopy

On the Taxonomic Resolution of Pollen and Spore Records of Earth’s Vegetation

3D Rotation-Invariant Description from Tensor Operation on Spherical HOG Field

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