Palm hand or palm, finger, fingernail, arm we are

Palm Reading is a traditional practice which is done in India and China .
Ancient records of
the frescoes in ruins of India and words given by  Brahmans has proved that palm reading was
very well liked in India at that time. Chiromancy is another name for palmistry. Palmistry
is not only used to read one’s hand or palm, it is also includes reading of arm
, finger and fingernail. By analysing one’s hand or palm, finger, fingernail, arm
we are able to identify about the character traits, health, wisdom, marriage and
many other aspects of a person.

Now-a-days
people prefer investing time in mobile applications. At present, there are lack
of mobile applications that allow palm reading to be done efficiently. So we
proposed to develop an mobile application that works effectively and
efficiently. Automatic Palm Reading is a mobile application which will be used to
learn a person’s fortune , future and personality. Automatic Palm Reading is based on Android
platform.

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Medical World is greatly influenced by the palm reading. The design,
implementation, and use of biomedical information systems in the form of
computer – aided decision support have become essential and widely used
over the last two decades. Medical scientists discovered that the hand can be
used as an indicator for medical problems and the palm is the reflection of
activities going on brain. The purpose of this application is to design and
implement a decision support model for healthcare on the basis of medical
palmistry to diagnose the diseases.

The algorithm starts with capturing of the palm image and extracting the
principle palm lines. Various image processing techniques like histogram
equalization, sharpening, masking, removing noise, etc. are applied on the
input images to get a clear sharpened image without noise. This helps in the
extraction of the palm lines. The palm lines
provide patterns that can be compared to past findings in predicting the
illnesses. . Fuzzy Inference
System is used to present medical knowledge as network diseases connected with
each other by logical relations. This
is beneficial for observing illnesses as it saves time and effort and provides
insights on further studies of the person’s health.The rest of the paper is
structured into 7 sections. In section 2 and 3, literature review of the
related work is presented. In section 4, the proposed methodology is presented
and details regarding the algorithm to be used is explained. In section 5, the
requirements are specified. In section 6, the future work and finally in
section 7 conclusion has been included.