Title :
Automatic color segmentation algorithms-with application to skin tumor feature identification
Author :
Umbaugh, Scott E. ; Moss, Randy H. ; Stoecker, William V. ; Hance, Gregory A.
Author_Institution :
Dept. of Electr. Eng., Southern Illinois Univ., Edwardsville, IL, USA
Abstract :
Two color-image segmentation methods are described. The first is based on a spherical coordinate transform of original RGB data. The second is based on a mathematically optimal transform, the principal components transform (also known as eigenvector, discrete Karhunen-Loeve, or Hotelling transform). These algorithms are applied to the extraction from skin tumor images of various features such as tumor border, crust, hair scale, shiny areas, and ulcer. The results of this research will be used in the development of a computer vision system that will seve as the visual front-end of a medical expert system to automate visual feature identification for skin tumor evaluation.<>
Keywords :
colour; image segmentation; medical image processing; skin; automatic color segmentation algorithms; color-image segmentation methods; computer vision system; crust; hair; mathematically optimal transform; medical diagnostic imaging; medical expert system; principal components transform; scale; shiny areas; skin tumor feature identification; spherical coordinate transform; tumor border; ulcer; Biological system modeling; Biomedical imaging; Data mining; Discrete transforms; Hair; Karhunen-Loeve transforms; Medical expert systems; Optical filters; Radio access networks; Skin neoplasms;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
