4,866 research outputs found
Curved Gabor Filters for Fingerprint Image Enhancement
Gabor filters play an important role in many application areas for the
enhancement of various types of images and the extraction of Gabor features.
For the purpose of enhancing curved structures in noisy images, we introduce
curved Gabor filters which locally adapt their shape to the direction of flow.
These curved Gabor filters enable the choice of filter parameters which
increase the smoothing power without creating artifacts in the enhanced image.
In this paper, curved Gabor filters are applied to the curved ridge and valley
structure of low-quality fingerprint images. First, we combine two orientation
field estimation methods in order to obtain a more robust estimation for very
noisy images. Next, curved regions are constructed by following the respective
local orientation and they are used for estimating the local ridge frequency.
Lastly, curved Gabor filters are defined based on curved regions and they are
applied for the enhancement of low-quality fingerprint images. Experimental
results on the FVC2004 databases show improvements of this approach in
comparison to state-of-the-art enhancement methods
The Filament Sensor for Near Real-Time Detection of Cytoskeletal Fiber Structures
A reliable extraction of filament data from microscopic images is of high
interest in the analysis of acto-myosin structures as early morphological
markers in mechanically guided differentiation of human mesenchymal stem cells
and the understanding of the underlying fiber arrangement processes. In this
paper, we propose the filament sensor (FS), a fast and robust processing
sequence which detects and records location, orientation, length and width for
each single filament of an image, and thus allows for the above described
analysis. The extraction of these features has previously not been possible
with existing methods. We evaluate the performance of the proposed FS in terms
of accuracy and speed in comparison to three existing methods with respect to
their limited output. Further, we provide a benchmark dataset of real cell
images along with filaments manually marked by a human expert as well as
simulated benchmark images. The FS clearly outperforms existing methods in
terms of computational runtime and filament extraction accuracy. The
implementation of the FS and the benchmark database are available as open
source.Comment: 32 pages, 21 figure
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