Title :
A Novel SVM Based Food Recognition Method for Calorie Measurement Applications
Author :
Pouladzadeh, Parisa ; Villalobos, Gregorio ; Almaghrabi, Rana ; Shirmohammadi, Shervin
Author_Institution :
Distrib. Collaborative Virtual Environ. Res. Lab., Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
Emerging food classification methods play an important role in nowadays food recognition applications. For this purpose, a new recognition algorithm for food is presented, considering its shape, color, size, and texture characteristics. Using various combinations of these features, a better classification will be achieved. Based on our simulation results, the proposed algorithm recognizes food categories with an approval recognition rate of 92.6%, in average.
Keywords :
image colour analysis; image recognition; image texture; support vector machines; SVM based food recognition; calorie measurement applications; classification method; color characteristics; food recognition applications; shape characteristics; size characteristics; texture characteristics; Feature extraction; Image color analysis; Image segmentation; Shape; Support vector machines; Thumb; Training; Calories measurement; Food recognition; Shape; Support vector machine (SVM); color; size and texture detection;
Conference_Titel :
Multimedia and Expo Workshops (ICMEW), 2012 IEEE International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-2027-6
DOI :
10.1109/ICMEW.2012.92
