Segmentation in Food Images

Segmentation in Food Images

Domingo Mery (Pontificia Universidad de Catolica de Chile, Chile) and Franco Pedreschi (Universidad de Santiago de Chile, Chile)
Copyright: © 2006 |Pages: 15
DOI: 10.4018/978-1-59140-753-9.ch016
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In this chapter, a robust algorithm for segmenting food imagery from a background is presented using colour images. The proposed method has three steps: (i) computation of a high contrast grey value image from an optimal linear combination of the RGB colour components; (ii) estimation of a global threshold using a statistical approach; and (iii) a morphological operation in order to fill the possible holes presented in the segmented binary image. Although the suggested threshold separates the food image from the background very well, the user can modify it in order to achieve better results. The algorithm was implemented in Matlab and tested on 45 images taken under very different conditions. The segmentation performance was assessed by computing the area Az under the Receiver Operation Characteristic (ROC) curve. The achieved performance was Az = 0.9982.

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