This is the authors' abstract. We don't add key points for this paper.
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%.
No takes yet. Share an insight, caveat, or question.
Ousman et al. (2019) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: