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

fYear

2012

fDate

9-13 July 2012

Firstpage

495

Lastpage

498

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia and Expo Workshops (ICMEW), 2012 IEEE International Conference on

Conference_Location

Melbourne, VIC

Print_ISBN

978-1-4673-2027-6

Type

conf

DOI

10.1109/ICMEW.2012.92

Filename

6266433