Evaluation of Color Based Keypoints and Features for the Classification of Melanomas Using the Bag-of-Features Model

Dermatologists consider color as one of the major discriminative aspects of melanoma. In this paper we evaluate the importance of color in the keypoint 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].