4,356 research outputs found
Fingerprint Identification - New Directions
In most of the algorithms that have been suggested in this report, the fingerprint image is reduced to a relatively short sequence of integers. This reduces the memory size required by the database. Each algorithm is intended to exploit specific properties and features of the fingerprint that vary from finger to finger, and that can be localized relatively fast using digital techniques, thus also reducing the computational time requirements to a minimum. In each case, the sensitivity of the algorithm to small variations in the image was also discussed, with the aim of reducing the False Rejection Rate, and of increasing the general robustness of the algorithm
Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface.
Sliding friction between the skin and a touched surface is highly complex, but lies at the heart of our ability to discriminate surface texture through touch. Prior research has elucidated neural mechanisms of tactile texture perception, but our understanding of the nonlinear dynamics of frictional sliding between the finger and textured surfaces, with which the neural signals that encode texture originate, is incomplete. To address this, we compared measurements from human fingertips sliding against textured counter surfaces with predictions of numerical simulations of a model finger that resembled a real finger, with similar geometry, tissue heterogeneity, hyperelasticity, and interfacial adhesion. Modeled and measured forces exhibited similar complex, nonlinear sliding friction dynamics, force fluctuations, and prominent regularities related to the surface geometry. We comparatively analysed measured and simulated forces patterns in matched conditions using linear and nonlinear methods, including recurrence analysis. The model had greatest predictive power for faster sliding and for surface textures with length scales greater than about one millimeter. This could be attributed to the the tendency of sliding at slower speeds, or on finer surfaces, to complexly engage fine features of skin or surface, such as fingerprints or surface asperities. The results elucidate the dynamical forces felt during tactile exploration and highlight the challenges involved in the biological perception of surface texture via touch
Segmentation of Loops from Coronal EUV Images
We present a procedure which extracts bright loop features from solar EUV
images. In terms of image intensities, these features are elongated ridge-like
intensity maxima. To discriminate the maxima, we need information about the
spatial derivatives of the image intensity. Commonly, the derivative estimates
are strongly affected by image noise. We therefore use a regularized estimation
of the derivative which is then used to interpolate a discrete vector field of
ridge points ``ridgels'' which are positioned on the ridge center and have the
intrinsic orientation of the local ridge direction. A scheme is proposed to
connect ridgels to smooth, spline-represented curves which fit the observed
loops. Finally, a half-automated user interface allows one to merge or split,
eliminate or select loop fits obtained form the above procedure. In this paper
we apply our tool to one of the first EUV images observed by the SECCHI
instrument onboard the recently launched STEREO spacecraft. We compare the
extracted loops with projected field lines computed from
almost-simultaneously-taken magnetograms measured by the SOHO/MDI Doppler
imager. The field lines were calculated using a linear force-free field model.
This comparison allows one to verify faint and spurious loop connections
produced by our segmentation tool and it also helps to prove the quality of the
magnetic-field model where well-identified loop structures comply with
field-line projections. We also discuss further potential applications of our
tool such as loop oscillations and stereoscopy.Comment: 13 pages, 9 figures, Solar Physics, online firs
An Efficient Vein Pattern-based Recognition System
This paper presents an efficient human recognition system based on vein
pattern from the palma dorsa. A new absorption based technique has been
proposed to collect good quality images with the help of a low cost camera and
light source. The system automatically detects the region of interest from the
image and does the necessary preprocessing to extract features. A Euclidean
Distance based matching technique has been used for making the decision. It has
been tested on a data set of 1750 image samples collected from 341 individuals.
The accuracy of the verification system is found to be 99.26% with false
rejection rate (FRR) of 0.03%.Comment: IEEE Publication format, International Journal of Computer Science
and Information Security, IJCSIS, Vol. 8 No. 1, April 2010, USA. ISSN 1947
5500, http://sites.google.com/site/ijcsis
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