Objective bake assessment using image analysis and artificial intelligence

Leonard Hamey, Jeffrey Yeh, Clarence Ng

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution


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.
Original languageEnglish
Title of host publicationCereals '97 : proceedings of the 47th Australian Cereal Chemistry Conference held in Perth,14th to18th September, 1997
EditorsA. W. Tarr, A. S. Ross, C. W. Wrigley
Place of PublicationNorth Melbourne
PublisherRoyal Australian Chemical Institute
Number of pages5
ISBN (Print)0909589941
Publication statusPublished - 1997
EventAustralian Cereal Chemistry Conference (47th : 1997) - Perth, Australia
Duration: 14 Sep 199718 Sep 1997


ConferenceAustralian Cereal Chemistry Conference (47th : 1997)


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