Inspecting pizza topping percentage and distribution by a computer vision method

Abstract

Topping percentage and distribution are two major features in the quality inspection of pizzas. The extraction of these features highly depends on the segmentation quality of pizza images. However, complex visual features and wide varieties of pizzas make the segmentation task difficult. Traditional segmentation methods are found only partly suitable for most pizza images. Therefore, a new segmentation method was developed by using the region-based segmentation as a dominant method and combining the strengths of both thresholding and edge-based segmentation methods. For evaluating the evenness of topping distribution, a practical method of dividing a pizza image into several equal-area partitions was developed. The experimental results show that the computer vision method developed is suitable for many different types of pizzas with an accuracy of over 90% for measuring topping exposure percentage and distribution.