QUALITY INSPECTION OF BAKERY PRODUCTS USING A COLOR‐BASED MACHINE VISION SYSTEM

Abstract
Muffins were evaluated for color by visual examination and by development of a machine‐reading system coupled with discriminant analysis of the data acquired. A classification algorithm separated light from dark‐colored muffins. The system's precision was assessed by evaluating the color of 4 cm diameter muffins pregraded prior to the evaluation of color and without pregrading. Applied to 200 samples, the automated system was able to correctly classify 96% of the pregraded and 79% of the ungraded muffins. The algorithm procedure was able to classify muffins at an accuracy level better than 88% in most cases whereas quality decisions among inspectors varied by 20 to 30%. Critical to precision by the machine‐read procedure was control of the illumination.

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