Skin Disease Recognition using Texture Analysis

Skin Texture Recognition Using Neural Networks

Skin recognition is used in many applications ranging from algorithms for face detection, hand gesture analysis, and to objectionable image filtering. In this work a skin recognition system was developed and tested. While many skin segmentation algorithms relay on skin color, our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more effic...

IRIS Recognition Method Using Random Texture Analysis

In this paper, we present a fast, simple and very powerful method for identifying human beings based on features of their iris texture. A very simple approach is presented to extract texture features of highly random iris texture on the contrary to current approaches that use complex mathematical description of the iris texture for feature extraction. The proposed method is tested with more tha...

Enhanced Ulcer Recognition from Capsule Endoscopic Images Using Texture Analysis

Skin disease diagnosis based on tissue frequency information analysis using sonogram patterns

Abstract Background Today early detection of common cancer with modern smart calculation is the most interesting issue due to the increased chances of successful treatment. Skin cancer is a serious and dangerous complication that threatens the lives of many people and if not diagnosed in time, it will have bad consequences. It is the fifth most common cancer in the female population and...

Dynamic Texture Recognition Using Normal Flow and Texture Regularity

The processing, description and recognition of dynamic (time-varying) textures are new exciting areas of texture analysis. Many real-world textures are dynamic textures whose retrieval from a video database should be based on both dynamic and static features. In this article, a method for extracting features revealing fundamental properties of dynamic textures is presented. These features are b...