The aim of the food adulteration process is to alter the quality of food to attain personal gain. This is typically achieved by incorporating artificial colors, substances, and low-quality alternatives into the food, which can result in severe health issues for the public. Recent studies have demonstrated that contamination in food can lead to a range of problems, including digestive and long-term health issues. In order to address these challenges, it is necessary to take appropriate actions to raise consumer awareness through the use of advanced technologies. In food science and technology, computer vision has surfaced as a very effective technique, outperforming traditional detection methods with fewer experts and reduced time requirements. This paper delves into consumer knowledge of food adulteration, assesses the progression from conventional to advanced adulteration detection methods, employs a comparison model that emphasizes the significance of computer vision in this field. This survey updates researchers about the necessity of vision-based systems and its role in increasing consumer awareness about food contamination and adulteration.