2017
DOI: 10.5370/jeet.2017.12.1.436
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Texture Based Automated Segmentation of Skin Lesions using Echo State Neural Networks

Abstract: -A novel method of Skin lesion segmentation based on the combination of Texture and Neural Network is proposed in this paper. This paper combines the textures of different pixels in the skin images in order to increase the performance of lesion segmentation. For segmenting skin lesions, a two-step process is done. First, automatic border detection is performed to separate the lesion from the background skin. This begins by identifying the features that represent the lesion border clearly by the process of Text… Show more

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Cited by 6 publications
(2 citation statements)
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“…Similar works dealing with ESN features extraction for image segmentation were reported in [12,17,18,19]. Other works propose to train ESN to classify image pixels based on their preliminary extracted features [2,8,9,10,13,14]. However, these works are focused on colour image segmentation and few of them applied the original approach from [4].…”
Section: Introductionmentioning
confidence: 92%
“…Similar works dealing with ESN features extraction for image segmentation were reported in [12,17,18,19]. Other works propose to train ESN to classify image pixels based on their preliminary extracted features [2,8,9,10,13,14]. However, these works are focused on colour image segmentation and few of them applied the original approach from [4].…”
Section: Introductionmentioning
confidence: 92%
“…A digit of major color, features has been projected in the literatures, including color histogram [15,16], color moments (CM) [17], color coherence vector (CCV) and color correlogram [18], etc. Among them, CM is one of the simplest yet very effective features.…”
Section: Color Featuresmentioning
confidence: 99%