Preprint Article Version 1 This version is not peer-reviewed

Orthogonal Moment Extraction and Classification of Melanoma Images

Version 1 : Received: 15 March 2018 / Approved: 16 March 2018 / Online: 16 March 2018 (05:26:31 CET)

How to cite: Singh, S.; Urooj, S. Orthogonal Moment Extraction and Classification of Melanoma Images. Preprints 2018, 2018030128 (doi: 10.20944/preprints201803.0128.v1). Singh, S.; Urooj, S. Orthogonal Moment Extraction and Classification of Melanoma Images. Preprints 2018, 2018030128 (doi: 10.20944/preprints201803.0128.v1).

Abstract

This paper provides orthogonal moments (OM) such as, Zernike Moments(ZM), Psuedo Zernike Moments(PZM) and Orthogonal Fourier Mellin Moments(OFMM) for the analysis of melanoma images. The moment invariants may vary with respect to geometric variations. For the analysis of orthogonal moments hundred random melanoma images and hundred non-melanoma images have been taken into consideration from the database of 570 melanoma images and 250 non-melanoma images respectively. Orthoganal moments have been computed by varying the phase angles from 10° to 40° with an equal interval of 10° degree for the orders 2, 4,8,16,32,64,128,256 respectively. For the optimal OMs Particle Swarm Optimization (PSO) technique have been used. These set of extracted optimal OMs have been further applied to classify melanoma images. Support Vector Machine (SVM) has been used for the classification of [1]sensitivity=88.78%.

Subject Areas

moments invariants; ZM,PZM; OFMM; SVM; PSO

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.