Silat Logo Recognition System

Firstly, I would like to express my deep thankfulness to my supervisor, Dry. Sarsaparillas Bat Nordic for her guidance, advise, criticism and correction throughout the progress of this project. Special appreciation also goes to my examiner and ASPICS lecturer for giving e supportive comments in order to enhance this proposed project. I also want to thank to my parents because they never stop giving morale support and for most, without their prayers and bless I wouldn’t have this enthusiast.

Last but not least, I would like to give my gratitude to my precious friends and classmates for being very helpful and willing to share and taught me things that were new and I’m weak at. Thank you very much. ABSTRACT Sisal is martial art that has been practiced in Malaysia since ages ago. Since there are no serious actions taken by Malaysian authorities, there exist some responsible people who use sisal name and logo to cheat people and do bad things such as fraud and superstitious thing.

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The aim of this project is to help people who interested in joining any sisal organization to differentiate which organization is the original and the fake one through the recognition of the logo and give information about sisal. The problem statement of this project is common people who have little knowledge about sisal find it hard to differentiate between registered and non-registered organization because of the design, color and the shape of the original logo and fake logo is quite minimal.

In order to get this project done, there are some steps that have been taken which include identification of sisal types, the features of sisal logo. Besides, define suitable AAA technique for image recognition, and logo identification. Second step is for data collection and analysis image of logo. Next is the designation of system architecture and system flow, Ass’s algorithm for main system components and interface for Sisal Logo Recognition System. Ghastly, the evaluation of system development includes interaction, data pre- processing, training and testing the accuracy of the system.