Survey of texture based feature extraction for skin disease detection

Authors:

Abstract
Skin diseases are most common form of infections occurring in people of all ages. As the costs of dermatologists to monitor every patient is very high, there is a need for a computerized system to evaluate patient's risk of skin disease using images of their skin lesions. Many researchers have used different preprocessing, segmentation and classification techniques to determine whether a skin image suffers from diseases or not. Feature extraction is very important for predictive modeling applications. Feature extraction in image processing is a method of capturing visual content of images for indexing and retrieval. Primitive image features can be either general features, such as extraction of color, texture and shape or domain specific features. Texture based features are widely used in image analysis for medical diagnosis. This paper presents a comprehensive survey of texture based feature extraction for detection of skin diseases and proposes a system based on the findings.

This publication has 5 references indexed in Scilit: