While it is now common practice to use a trend removal to eliminate low frequency xed pattern noise in
thermal imaging systems, there is still some disagreement as to whether one means of trend removal is better
than another and whether or not the strength of the trend removal should be limited. The dierent methods
for trend removal will be presented as well as an analysis of the calculated noise as a function of their strengths
will be presented for various thermal imaging systems. In addition, trend removals were originally put in place
in order to suppress the low-frequency component of the Sigma VH term. It is now prudent to perform a trend
removal at an intermediate noise calculation step in order to suppress the low frequency component of both the
Sigma V and Sigma H components. A discussion of the ramications of this change in measurement will be
included for thermal modeling considerations.
A universal implementation for most behavioral Biometric systems is still unknown since some behaviors aren't individual
enough for identification. Habitual behaviors which are measurable by sensors are considered 'soft' biometrics (i.e., walking
style, typing rhythm), while physical attributes (i.e., iris, fingerprint) are 'hard' biometrics. Thus, biometrics can aid in the
identification of a human not only in cyberspace but in the world we live in. Hard biometrics have proven to be a rather
successful form of identification, despite a large amount of individual signatures to keep track of. Virtually all soft biometric
strategies, however, share a common pitfall. Instead of the classical pass/fail decision based on the measurements used by hard
biometrics, a confidence threshold is imposed, increasing False Alarm and False Rejection Rates. This unreliability is a major
roadblock for large scale system integration. Common computer security requires users to log-in with a six or more digit PIN
(Personal Identification Number) to access files on the disk. Commercially available Keystroke Dynamics (KD) software can
separately calculate and keep track of the mean and variance for each time travelled between each key (air time), and the time
spent pressing each key (touch time). Despite its apparent utility, KD is not yet a robust, fault-tolerant system. We begin with a
simple question: how could a pianist quickly control so many different finger and wrist movements to play music? What
information, if any, can be gained from analyzing typing behavior over time? Biology has shown us that the separation of arm
and finger motion is due to 3 long nerves in each arm; regulating movement in different parts of the hand. In this paper we wish
to capture the underlying behavioral information of a typist through statistical memory and non-linear dynamics. Our method may reveal an inverse Compressive Sensing mapping; a unique individual signature.
The next generation of night vision goggles will fuse image intensified and long wave infra-red to create a hybrid image that will enable soldiers to better interpret their surroundings during nighttime missions. Paramount to the development of such goggles is the exploitation of image quality measures to automatically determine the best image fusion algorithm for a particular task. This work will introduce a novel monotonic correlation coefficient to investigate how well possible image quality features correlate to actual human performance, which is measured by a perception study. The paper will demonstrate how monotonic correlation can identify worthy features that could be overlooked by the traditional Pearson correlation.
The U.S. Army RDECOM CERDEC Night Vision & Electronic Sensors
Directorate has developed a laser-range-gated imaging system
performance model for the detection, recognition, and identification
of vehicle targets. The model is based on the established US Army
RDECOM CERDEC NVESD sensor performance models of the human system
response through an imaging system. The Java-based model, called
NVLRG, accounts for the effect of active illumination, atmospheric
attenuation, and turbulence effects relevant to LRG imagers, such as
speckle and scintillation, and for the critical sensor and display
components. This model can be used to assess the performance of
recently proposed active SWIR systems through various trade studies.
This paper will describe the NVLRG model in detail, discuss the
validation of recent model components, present initial trade study
results, and outline plans to validate and calibrate the end-to-end
model with field data through human perception testing.