In this paper we describe an image segmentation method for segmenting food items in images used for dietary assessment. Dietary assessment methods used to determine the foods and beverages consumed at a meal are essential for understanding the link between diet and health. Snakes, or active contours, are used extensively to locate object boundaries and segment images. Experimental results using classical snakes on food images show the problems associated with contour initialization and poor detection performance for food images. In this paper, we explore various methods of contour initialization and integrate a background removal method to improve the performance of food image segmentation. We describe the details of the proposed food image segmentation method and also evaluate our segmentation approach on food images.