Objective bake assessment using image analysis and artificial intelligence

Bake assessment in food manufacture is currently performed by trained human inspectors. The subjective nature of human assessment introduces short-term variation and long-term drift of bake standards due to inconsistencies in human performance. A durable, repeatable and transferable assessment method is desirable to ensure long-term consistency of product bake and to facilitate product migration between manufacturing sites. These goals are successfully met by employing computer analysis of colour digital images to assess product bake. Our studies have shown the existence of a baking curve, unique to each product, which describes the colour development of that product during baking. Based upon this discovery, a system has been developed employing Artificial Intelligence techniques, specifically Artificial Neural Networks, to match computer bake assessment to one or more expert bake assessors. The process of training the system for a particular product is driven by these assessors who select and classify product samples. By this means, the system can be deployed across the product range with minimal involvement of image analysis and computing technologists. The system has been shown to provide significant performance improvements in the bake quality assessment task.