Open AccessExtraction of melanoma 3d features from tensor representation
Author(s) -
N S Sushmita,
Gururaj Murtugudde,
T Y Satheesha
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.9.10012
Subject(s) - tensor (intrinsic definition) , representation (politics) , computer science , rgb color model , artificial intelligence , point (geometry) , event (particle physics) , pattern recognition (psychology) , computer vision , mathematics , physics , pure mathematics , geometry , politics , political science , law , quantum mechanics
Melanoma is one of the unsafe growth to be dealt with too to recognize in introductory stage. Here we take the skin sore by ROI and after that we take out highlights of it then it should be sectioned whether the specific picture is malignant or not. In the event that it is destructive at that point group the extricated includes and examine about kind of stages. This paper presents a non-obtrusive electronic dermoscopy framework that considers the evaluated profundity of skin sores for determination. For test assessments, the PH2 and ATLAS dermoscopy datasets is considered. A novel 3D remaking calculation from 2D dermoscopic pictures is proposed. Here we remove the 3D highlights from tensor portrayal. The discovery of 3D picture shape and RGB are to be done. In this paper, we have proposed this work for 3D profundity parameter, which will improve the grouping rate.