Journal
PATTERN RECOGNITION LETTERS
Volume 28, Issue 2, Pages 260-267Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2006.07.012
Keywords
Gabor wavelets; jets; Euclidean Distance; normalised scalar product; hierarchical classifier; Gabor similarity maps; road sign recognition
Categories
Ask authors/readers for more resources
In recent years it has been shown that hierarchical classifiers have a significant advantage over single stage classifiers both in classification accuracy and in complexity of the classification features. This paper introduces a new method for creating the structure of hierarchical classifiers using a novel method for determining clusters. The proposed method uses features obtained using Gabor wavelets to create similarity maps, which help separating the class space into smaller more distinctive clusters. This approach has been applied on the Road Sign Recognition problem and has shown encouraging results in comparison to k-means algorithm. (c) 2006 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available