On Comparing Color Spaces for Food Segmentation

  • Sinem AslanEmail author
  • Gianluigi Ciocca
  • Raimondo Schettini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10590)


Accurate segmentation of food regions is important for both food recognition and quantity estimation and any error would degrade the accuracy of the food dietary assessment system. Main goal of this work is to investigate the performance of a number of color encoding schemes and color spaces for food segmentation exploiting the JSEG algorithm. Our main outcome is that significant improvements in segmentation can be achieved with a proper color space selection and by learning the proper setting of the segmentation parameters from a training set.


Automatic food segmentation Color spaces JSEG 


  1. 1.
    Anthimopoulos, M., Dehais, J., Diem, P., Mougiakakou, S.: Segmentation and recognition of multi-food meal images for carbohydrate counting. In: Proceedings of the IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE 2013), pp. 1–4 (2013)Google Scholar
  2. 2.
    Bettadapura, V., Thomaz, E., Parnami, A., Abowd, G.D., Essa, I.: Leveraging context to support automated food recognition in restaurants. In: Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2015), pp. 580–587 (2015)Google Scholar
  3. 3.
    Ciocca, G., Napoletano, P., Schettini, R.: Food recognition: a new dataset, experiments, and results. IEEE J. Biomed. Health Inform. 21(3), 588–598 (2017)CrossRefGoogle Scholar
  4. 4.
    Lee, D., Plataniotis, K.N.: A taxonomy of color constancy and invariance algorithm. In: Celebi, M.E., Smolka, B. (eds.) Advances in Low-Level Color Image Processing. LNCVB, vol. 11, pp. 55–94. Springer, Dordrecht (2014). CrossRefGoogle Scholar
  5. 5.
    Ohta, Y.I., Kanade, T., Sakai, T.: Color information for region segmentation. Comput. Graph. Image Process. 13(3), 222–241 (1980)CrossRefGoogle Scholar
  6. 6.
    Shroff, G., Smailagic, A., Siewiorek, D.P.: Wearable context-aware food recognition for calorie monitoring. In: Proceedings of the 12th IEEE International Symposium on Wearable Computers (ISWC 2008), pp. 119–120 (2008)Google Scholar
  7. 7.
    He, Y., Khanna, N., Boushey, C., Delp, E.: Image segmentation for image-based dietary assessment: a comparative study. In: Proceedings of the IEEE International Symposium on Signals, Circuits and Systems (ISSCS 2013), pp. 1–4 (2013)Google Scholar
  8. 8.
    Zhu, F., Bosch, M., Khanna, N., Boushey, C.J., Delp, E.J.: Multiple hypotheses image segmentation and classification with application to dietary assessment. IEEE J. Biomed. Health Inform. 19(1), 377–388 (2015)CrossRefGoogle Scholar
  9. 9.
    Matsuda, Y., Hoashi, H., Yanai, K.: Recognition of multiple-food images by detecting candidate regions. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME 2012), pp. 25–30 (2012)Google Scholar
  10. 10.
    Deng, Y., Manjunath, B.: Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. Pattern Anal. Mach. Intell. 23(8), 800–810 (2001)CrossRefGoogle Scholar
  11. 11.
    Deng, Y., Manjunath, B.: JSEG Project. (1999). Accessed 27 June 2017
  12. 12.
    Deng, Y., Kenney, C., Moore, M.S., Manjunath, B.: Peer group filtering and perceptual color image quantization. In: Proceedings of the IEEE International Symposium on Circuits and Systems, (ISCAS 1999), Vol. 4, pp. 21–24. IEEE (1999)Google Scholar
  13. 13.
    Duda, R.O., Hart, P.E., Stork, D.G., et al.: Pattern classification, vol. 2. Wiley, New York (1973)zbMATHGoogle Scholar
  14. 14.
    Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour detection and hierarchical image segmentation. IEEE Trans. Patt. Anal. Mach. Intell. 33(5), 898–916 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Sinem Aslan
    • 1
    Email author
  • Gianluigi Ciocca
    • 1
  • Raimondo Schettini
    • 1
  1. 1.Department of Informatics, Systems and CommunicationUniversity of Milano-BicoccaMilanoItaly

Personalised recommendations