Abstract
The importance of color information for the automatic diagnosis of skin tumors by computer vision is demonstrated. The utility of the relative color concept is proved by the results in identifying variegated coloring. A feature file paradigm is shown to provide an effective methodology for the independent development of software modules for expert system/computer vision research. An automatic induction tool is used effectively to generate rules for identifying variegated coloring. Variegated coloring can be identified at rates as high as 92% when using the automatic induction technique in conjunction with the color segmentation method
Recommended Citation
S. E. Umbaugh et al., "Applying Artificial Intelligence to the Identification of Variegated Coloring in Skin Tumors," IEEE Engineering in Medicine and Biology Magazine, Institute of Electrical and Electronics Engineers (IEEE), Jan 1991.
The definitive version is available at https://doi.org/10.1109/51.107171
Department(s)
Electrical and Computer Engineering
Second Department
Chemistry
Keywords and Phrases
Artificial Intelligence; Automatic Diagnosis; Automatic Induction Tool; Color Information; Color Segmentation Method; Computer Vision; Expert System; Expert Systems; Feature File Paradigm; Medical Diagnostic Computing; Skin; Skin Tumors; Software Modules; Variegated Coloring Identification
International Standard Serial Number (ISSN)
0739-5175
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1991 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 1991
