Using small checkerboards as size reference: A model-based approach

Abstract

Monitoring diet is crucial for preventing or dealing with many chronic diseases. Therefore, plenty of different methods have been developed to serve this purpose. Among these, automatic diet monitoring based on mobile devices are of particular interest. An automatic system is supposed to be able to detect type and amount of food intake. This work suggests using a small checkerboard in food images as size reference as an aid for estimating food amount. Although checkerboard is a simple pattern, most of the off-the-shelf algorithms do not perform well in detecting small checkerboards. This paper extends a previous work presenting a new stochastic model-based algorithm to detect small checkerboards. The algorithm first locates the checkerboard in the food image and then applies a customized corner detection algorithm to the located region. Experimental results show notably better performance in comparison to basic methods and to the previous version of the method.