Abstract
Palmistry technique is traditionally known as an ancient art of reading the palm and it can be found in many parts of the world. Since blood circulation in the palm contains valuable information about the health condition of a person, this technique is also acts as one of the aid tools for diagnosing purposes. This thesis will describes the development and analysis of palmistry technique using image processing in term primary additive color component (RGB). The analysis on palmistry will describe about personality of person which is social, non-social, intelligence, non-intelligence, sport and non-sport. Two major of work were carried out to get the result, first the extraction color from palmistry, this process will extract color to a single color component. In this work, samples of palm images are digitally captured under standard and control environment. Other characteristic parameters representing the subject’s personality and health are also taken. Statistical tools are applied to the quantified color component indices from the processed image for significant findings that can relate color of palm with respect to the subject’s character. Findings in this research shows the non-social type of personality can be discriminated from other type of personality based on R and G component refer to result from p-value. Another type also can be trace easily based on R component, all this result is justified by statistical test.
Metadata
Item Type: | Thesis (Degree) |
---|---|
Creators: | Creators Email / ID Num. Azman, Abdul Hadi UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Hashim, Hadzli UNSPECIFIED |
Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics > Pattern recognition systems |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering |
Programme: | Bachelor in Electrical Engineering (Hons) |
Keywords: | Palmistry, digital image processing, personality |
Date: | 2007 |
URI: | https://ir.uitm.edu.my/id/eprint/102877 |
Download
102877.pdf
Download (121kB)