Site Loader
Rock Street, San Francisco

Palmprint investigation has been studied by many people over
10 years. During this study, many different issues related to palmprint
recognition have been found and resolved. The papers related to palmprint
recognition provides an overview of palmprint research, describing in
particular capture devices, preprocessing, verification algorithms, palmprint-
related fusion, algorithms especially designed for real-time palmprint
identification in numerous databases and measures for protecting the users
privacy related to palmprint identification and many suggestions are offered.

The pictorial view of the surface of the palm normally
contains three flexion creases, secondary creases and ridges. The flexion
creases are also called principal lines and the secondary creases are called
wrinkles. The flexion and the major secondary creases are formed between the
third and fifth months of pregnancy 1 and superficial lines appear after
birth. Although the three major flexions are genetically dependent, but other
creases are not 2. Even identical twins have different palmprints 2. These
non-genetically deterministic and complex patterns are very useful in personal
identification. Human beings were interested in palm lines for fortune telling
long time ago and now also. Scientists found that palm lines are associated
with some genetic diseases including Down syndrome, Aarskog syndrome, Cohen
syndrome and fetal alcohol syndrome 68. Palmprint research employs either
high or low resolution images. High resolution images are suitable for forensic
applications such as criminal detection 3. Low resolution images are more
suitable for civil and commercial applications such as access control.
Generally, high resolution refers to 400 dpi or more and low resolution refers
to 150 dpi or less. Researchers can extract ridges, singular points and minutia
points as essential features from high resolution images while in low
resolution images they generally extract principal lines, wrinkles and texture.
Initially palmprint research focused on high-resolution images 4,5 but now
almost all research is working on low resolution images for civil and
commercial applications. The design of a biometric system takes account of five
objectives: cost, user acceptance and environment constraints, accuracy, com-
putation speed and security. Reducing accuracy can lead to increase of speed.
Typical examples are hierarchical approaches. Reducing user acceptance can help
in improving accuracy. For instance, users are required to provide more samples
for training. Increasing in cost can lead to enhance in security. We can embed
more sensors to collect different signals for liveness detection. In some
applications, environmental constraints such as memory usage, power
consumption, size of templates and size of devices have to be fulfilled. A biometric
system installed in Personal Digital Assistant requires low power and memory
consumption but these requirements may not be sufficient for biometric access
control systems. A practical biometric system should balance all of the above
aspects. A typical palmprint recognition system consists of five parts:
palmprint scanner, preprocessing, feature extraction, matcher and database. The
palmprint scanner function is to collect palmprint images. Preprocessing helps
in setting up a coordinate system to align palmprint images and to segment a part
of palmprint image for feature extraction. Feature extraction motive is to
obtain effective features from the preprocessed palmprints. A matcher compares
two palmprint features and a database stores registered templates.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now

Post Author: admin


I'm Dora!

Would you like to get a custom essay? How about receiving a customized one?

Check it out