Food image analysis: Segmentation, identification and weight estimation

We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes.

[1]  Xing Zhang,et al.  A mobile structured light system for food volume estimation , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[2]  Allan D. Jepson,et al.  Benchmarking Image Segmentation Algorithms , 2009, International Journal of Computer Vision.

[3]  B. S. Manjunath,et al.  Color and texture descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[4]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Edward J. Delp,et al.  Specular Highlight Removal for Image-Based Dietary Assessment , 2012, 2012 IEEE International Conference on Multimedia and Expo Workshops.

[6]  E. Delp,et al.  Multilevel segmentation for food classification in dietary assessment , 2011, 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA).

[7]  Martin R. Okos,et al.  Developing novel 3D measurement techniques and prediction method for food density determination , 2011 .

[8]  Edward J. Delp,et al.  Combining global and local features for food identification in dietary assessment , 2011, 2011 18th IEEE International Conference on Image Processing.

[9]  Mingui Sun,et al.  3D localization of circular feature in 2D image and application to food volume estimation , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  Daniel P. Huttenlocher,et al.  Image segmentation using local variation , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[11]  E J Delp,et al.  Use of technology in children’s dietary assessment , 2009, European Journal of Clinical Nutrition.

[12]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[13]  David S. Ebert,et al.  Volume estimation using food specific shape templates in mobile image-based dietary assessment , 2011, Electronic Imaging.

[14]  Edward J. Delp,et al.  Image enhancement and quality measures for dietary assessment using mobile devices , 2012, Electronic Imaging.