By Topic

Comparison of evolutionary and conventional feature extraction methods for malt classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ciesielski, V. ; Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Melbourne, VIC, Australia ; Lam, B. ; Minh Luan Nguyen

Our primary motivation in this paper is to determine whether evolved texture feature extraction programs are competitive with human derived programs for a difficult real world texture classification problem. The problem involves distinguishing images of three classes of bulk malt. There are subtle differences between the three classes. We have used a number of human derived methods, Haralick, Gabor, Haar, histogram and Galloway, to get feature vectors for the malt problem. We have also used a number of feature extraction programs that were evolved from thirteen Brodatz textures. We performed classification with a 1 nearest neighbour classifier. The evolved features gave an accuracy of 67% which is considerably better than the 53% achieved with the Haar features, but not as good as the 77% achieved with the Galloway features. Analysis of the evolved features suggested that they are capturing some texture regularities not captured by the human derived methods. We conclude that the evolved features are competitive with the human derived features and can provide enhanced accuracy when used in conjunction with human derived features.

Published in:

Evolutionary Computation (CEC), 2012 IEEE Congress on

Date of Conference:

10-15 June 2012