Abstract
The idea of adding an auto-recognition feature for Malay Festive Seasons Food based on images is very challenging task in mage computer vision as it is something new and undiscovered before. However, this recognition is important for Malaysian users to manage calorie intake, especially during Hari Raya, one of the biggest festive seasons and the most celebrated festivals in Malaysia. As color plays an important role in differentiating the type of food, therefore this research aims to implement Color Feature Extraction Method after performing segmentation techniques during the pre-processing phase where each color from the images will be extracted individually. Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification which is the part of the Support Vector Machine (SVM) algorithm. The reliability and effectiveness of the classifier are evaluated through system testing where the total overall percentage of correct recognition performed by the system is 82.5% according to the correct and wrong recognition obtained. The ability to recognize the food correctly after classifying the image is crucial in this research to accurately perform the calorie estimation whereby the calorie value will be auto- generated after food recognition is performed. Besides, thorough research has been conducted on the calorie value for each type of food by using the reliable internet resources to ensure users can benefit from the system in the future.
Metadata
Item Type: | Thesis (Degree) |
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Creators: | Creators Email / ID Num. Basiruddin, Nurul Hafiza 2020974015 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Zulkifli, Zalikha UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Computer software > Application software Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Computer software > Integrated software |
Divisions: | Universiti Teknologi MARA, Perak > Tapah Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Computer Science |
Keywords: | Food recognition; calorie detection; Color Feature Extraction Method; Error-Correcting Output Codes |
Date: | July 2021 |
URI: | https://ir.uitm.edu.my/id/eprint/59371 |
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