Fusion of structural and textural features for melanoma recognition

• Published in: IET computer vision Vol. 12; no. 2; pp. 185 - 195
• Main Authors: Adjed, Faouzi, Safdar Gardezi, Syed Jamal, Ababsa, Fakhreddine, Faye, Ibrahima, Chandra Dass, Sarat
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.03.2018; IET; Wiley
• Subjects: cancer; cancers; dermoscopy; Engineering Sciences; feature extraction; image fusion; image recognition; local binary pattern operator; medical image processing; melanoma recognition; Review Article; Signal and Image processing; structural features; support vector machine; support vector machines; SVM classifier; textural features; wavelet transforms; support vector machines; wavelet transforms; image fusion; structural features; local binary pattern operator; textural features; support vector machine; feature extraction; cancers; cancer; melanoma recognition; SVM classifier; medical image processing; image recognition; dermoscopy

Melanoma is one the most increasing cancers since past decades. For accurate detection and classification, discriminative features are required to distinguish between benign and malignant cases. In this study, the authors introduce a fusion of structural and textural features from two descriptors. T...