Reconstruction Error Analysis of Skin Lesion Images using Orthogonal Moments
Sudhakar Singh1, Masood Alam2, Shabana Urooj3
1Sudhakar Singh, Department of Biomedical Engineering, LPU, Phagwara, Punjab, India.
2Masood Alam, Department of Mathematics and IT, Centre for Prepatory Studies, Sultan Qaboos University, Muscat, Sultanate of Oman Shabana.
3Urooj, Department of Electrical Engineering, Gautam Buddha University, Greater Noida, U.P., India.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 10910-10915 | Volume-8 Issue-4, November 2019. | Retrieval Number: C4795098319/2019©BEIESP | DOI: 10.35940/ijrte.C4795.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Orthogonal moments (OMs) are amongst the superlative region centered shape descriptors. These OMs retain lowest facts redundancy. Zernike Moments (ZM) and pseudo Zernike Moments (PZM) are tested with respect to rotation invariance, and scale invariance for skin lesion images. Image reconstruction is executed for various orders of two different orthogonal moments; ZM and PZM. Reconstruction errors are also computed. This paper examines the impact of these errors on the features of OMs and executes a relative study of these errors on the precise calculation of the two major OMs: ZMs and PZMs.
Keywords: Orthogonal Moments Invariants, ZM, PZM, PSO SVM.
Scope of the Article: Image Processing and Pattern Recognition.