Bag-of-Features Classification Model for the Diagnose of Melanoma in Dermoscopy Images Using Color and Texture Descriptors

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Catarina Barata (Author) Other; Jorge S Marques (Author) Other; Teresa Mendonca (Author) FCUP

Conference proceedings International

Title: IMAGE ANALYSIS AND RECOGNITION

Pages: 547-555

10th International Conference on Image Analysis and Recognition (ICIAR)

Pvoa do Varzim, PORTUGAL, JUN 26-28, 2013

Indexing

ISI Web of Knowledge - 22 Citations

Scopus - 33 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-008-E9R

DOI: 10.1007/978-3-642-39094-4_62

Abstract (EN): Melanoma detection using medical oriented approaches has been a trend in skin cancer research. This paper uses a Bag-of-Feature model for the detection of melanomas in dermoscopy images and aims at identifying the role of different local texture and color descriptors. This is a medical oriented approach and the reported results are promising (Sensitivity = 93%, Specificity=85%), showing the ability of this method to describe medical dermoscopic features. Moreover, the results show that color descriptors outperform texture ones.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9