Food Non-Destructive Quality Evaluation Using Color Image Analysis System

Abstract

Quality inspection of food and agricultural product are difficult and labor-intensive. Simultaneously, with increased expectations for food products of high quality and safety standards, the need for accurate, fast and objective quality determination of these characteristics in food products continues to grow. However, these operations generally in Cameroon are manual which is costly as well as unreliable because the human decision in identifying quality factors such as appearance, flavor, nutrient, texture, is inconsistent, subjective and slow. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique to accomplish these requirements. This inspection approach based on image analysis and processing has an important place in the food industry. The application of color image analysis system, in this case, shows clearly that all the food product studied here were discriminated over 95%.