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Halal is the term used for permissible food according to Islamic dietary law. Indicators such as Halal logo have been used to facilitate Muslims in identifying Halal food. In Malaysia, the Department of Islamic Development (JAKIM) has introduced a standard Halal logo for locally manufactured products and currently recognizes 67 Islamic bodies in 41 countries around the world as certification bodies for products imported into Malaysia. Therefore, a more practical way is required to assist Muslims in recognizing various forms of Halal logos on food packaging. A neural network (NN) approach is proposed to recognize authentic and recognized Halal logo on imported products. A dataset of available and recognized Halal logo images worldwide will be created for this purpose. The dataset will be used to train and test the performance of the learning algorithm to recognize logo of recognized foreign bodies by JAKIM. The approach is expected to complement current facilities for verification using Short Messaging Services (SMS) and web portal. The approach is assumed to be more efficient and accurate for Halal logo verification which eventually could win the trust of Halal product consumers and support the Halal industry in Malaysia.
Razak et al. (Mon,) studied this question.