Segmentation and grading of eczema skin lesions

Author

Yau Kwang Ch´ng ; Nisar, Humaira ; Vooi Voon Yap ; Kim Ho Yeap ; Jyh Jong Tang

Author_Institution

Dept. of Electron. Eng., Univ. Tunku Abdul Rahman, Kampar, Malaysia

fYear

2014

fDate

15-17 Dec. 2014

Firstpage

1

Lastpage

5

Abstract

In this paper Eczema skin lesions are segmented and graded using image processing and analysis. For preprocessing adaptive light compensation and gamma correction has been used. The effect of color space normalization has been studied for lesion segmentation. K-means algorithm is used for segmentation. We have used RGB and CIELab color models; and their normalized I and II versions. The experimental results show that normalized color spaces give better segmentation results than the normal color spaces. Our proposed algorithm gives best segmentation accuracy of 84.6% for RGB normalized II color space for the G channel for adaptive light compensation. The grading accuracy for erythema is around 70%.

Keywords

image colour analysis; image segmentation; medical image processing; skin; CIELab color models; G channel; K-means algorithm; RGB color models; RGB normalized II color space; adaptive light compensation preprocessing; color space normalization; eczema skin lesion grading; eczema skin lesion segmentation; erythema; gamma correction; image analysis; image processing; Accuracy; Colored noise; Image color analysis; Image segmentation; Lesions; Skin; Vectors; color spaces; grading; segmentation; skin lesions;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communication Systems (ICSPCS), 2014 8th International Conference on

Conference_Location

Gold Coast, QLD

Type

conf

DOI

10.1109/ICSPCS.2014.7021131

Filename

7021131