Title
Evaluation of Color Based Keypoints and Features for the Classification of Melanomas Using the Bag-of-Features Model.
Abstract
Dermatologists consider color as one of the major discriminative aspects of melanoma. In this paper we evaluate the importance of color in the key-point detection and description steps of the Bag-of-Features model. We compare the performance of gray scale against that of color sampling methods using Harris Laplace detector and its color extensions. Moreover, we compare the performance of SIFT and Color-SIFT patch descriptors. Our results show that color detectors and Color-SIFT perform better and are more discriminative achieving Sensitivity = 85%, Specificity = 87% and Accuracy = 87% in PH2 database [17].
Year
DOI
Venue
2013
10.1007/978-3-642-41914-0_5
ADVANCES IN VISUAL COMPUTING, ISVC 2013, PT I
Keywords
Field
DocType
Melanoma,Dermoscopy,Bag-of-Features,Color Based Keypoints,Harris Laplace detector,SIFT,Color-SIFT
Computer vision,Scale-invariant feature transform,Pattern recognition,Computer science,Bag of features,Artificial intelligence,Sampling (statistics),Discriminative model,Detector,Grayscale
Conference
Volume
ISSN
Citations 
8033
0302-9743
6
PageRank 
References 
Authors
0.49
10
3
Name
Order
Citations
PageRank
Catarina Barata11069.98
Jorge S. Marques260.49
Jorge Rozeira31327.44