Intelligent garment system using fuzzy expert system / Amal Nabilah Md Amin
Body measurement is the most important thing that need to be considered in order to find the best fit size clothes. Traditionally, manual taking measurement by tailor has been applied. However, this conventional method requires more time and energy. This method also involved highly cost which...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/1368/2/1368.pdf |
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| Summary: | Body measurement is the most important thing that need to be considered in order to
find the best fit size clothes. Traditionally, manual taking measurement by tailor has
been applied. However, this conventional method requires more time and energy. This
method also involved highly cost which may give a huge impact to the garment
company. Therefore, a new system should be developed to measure human body based
on the data (image) given by the customers. It will help to search and decide the best fit
cloth(es) as a result. This research use one of the artificial intelligence techniques,
Fuzzy Expert System. The type of fiizzy inference applied to the system is Mamdani
with hedges. The &tst step applied is by defining the range of body measurement for
each clothes size which was determined by the relevant expertise (tailor). Then fiizzy
rules and fiizzy sets are determiaed. Next, coordinate point used for the image before
the system gathers the measurement of the body. After that, the measurement will
become an input to the knowledge base. The system will tiien be able to determine the
match clothes size. This project was restricted to the Quppy's Garment Sdn Bhd for the
shoulder, chest, waist and hip range measurement. This project is significant to the
garment industry whereby, in defining clothes sizes using intelligent systems may make
process faster and decrease the cost. The system have been tested base on 30 images
and 95% of the output generate are consistent. |
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