The ever increasing consumer needs and quality requirements have led to the necessity for more objective and accurate assessment of individual pizza topping quantity and distribution. In the current study the use of computer vision for the evaluation of different features of pizza topping quality were assessed. The indexes used for the analysis of the twenty-five samples examined included ham area percentage, mushroom area percentage and topping area percentage (TAP). A fuzzy logic system was then developed and used to classify the pizza topping quality, in comparison with quality personnel assessment. The TAP index gave the lowest ambiguous degree value hence indicating that it displays the least fuzzyness. A classification error of 24% was determined for the five linguistic personnel classes. When only two-classification levels (i.e. acceptable quality and defective quality) were considered an accuracy of 100% was achieved. (C) 2002 Elsevier Science Ltd. All rights reserved.