Computer Vision Approach for Detecting Adulteration of Ghee with Foreign Fats – A Survey

Abstract

Ghee is pure clarified fat derived from milk, yogurt and fresh cream. It is most commonly used milk fat product in India. The consumption and production of ghee is consistently increasing by 10% in our country in every year. In comparison to other milk fat product, ghee is expensive and short in demand because of its pleasant taste or high nutrition value. Due to its high cost and demand in market, there are high possibilities to adulterate it with cheap fats like vegetable oil/animal body fats. The adulteration detection of ghee is becoming a serious issue to chemists. Several analytical and instrumental methods are available for the detecting adulteration in ghee based on chemical principles. On the basis of study, it was observed that analytical methods are not suitable to detect the adulteration level of <15%. In recent time, digital image analysis is introduced in the field of adulteration detection in food products. A very few studies found in the area of milk fat adulteration detection with foreign fats using image analysis. Various studies found related to detection of adulteration in Oils (like Extra virgin olive oil, sesame oil etc.) with cheap oil using the various color models (like CIELAB, RGB, HSV, CMYK) and machine learning algorithms.