An Application of SURF Algorithm on JAKIM’s Halal Logo Detection

Abstract

Halal logo plays an important role in influencing Muslim consumer’s level of confidence in the Halal status of a product. However, certified Halal logo can be easily manipulated. Besides, detecting and recognizing the credibility of the logo is visually challenging without any computer-vision assistance. Therefore, an automated system is indeed in need to detect and verify the authenticity of the logo. This study proposed the application of Speeded Up Robust Features (SURF) algorithm in detecting various images of Halal logo, which then was matched with the reference image of certified Halal logo by JAKIM. Accuracy rate of the detected image was then calculated. A total of 100 images of certified logo and fake Halal logo gathered from various resources were used. Testing set which are independent of the training set were used and managed to attain 85.71% of accuracy rate. The experiments show that the proposed method achieved the desirably good result and was able to be at par with other existing methods.