Automatic Detection of Inorganic Substances in Vegetables and Fruits

Abstract

As the expectation for higher quality of life necessity increases, consumers have greater demands for quality food. Food authentication is the technical means of ensuring food is what it expresses on the labels. A popular approach to food authentication is based on spectroscopy method .This approach is non-destructive and efficient but not cost-effective. This paper presents a computer vision-based sensor system for food authentication, i.e., differentiating organic from non-organic Fruits. This sensor system consists of pattern recognition software and cost-effective Hardware. These diffraction images are then converted into a data matrix for classification by pattern recognition algorithms, including k-nearest neighbors (k-NN) and support vector machine (SVM) .In this methodology we carry out experiments on a reasonable collection of fruit and vegetable samples and employ a proper pre-processing, which results in a highest classification accuracy in class. Our studies conclude that this sensor system has the potential to provide a viable solution to empower consumers in fruits and vegetable authentication.