Knowledge-based color and texture analysis of skin image

Atam P. Dhawan, Mehul Parikh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


The color and texture of the surface pigmentation pattern of skin images provide important diagnostic and prognostic features for detection of lethal skin-cancer. Since intensity as well as texture are important in this application, the segmentation algorithm is required to incorporate both of them in the process of region extraction and description. A multichannel segmentation scheme is presented here, in which the intensity-based segmentation is obtained using the modified pyramid-based region extraction algorithm while the texture-based segmentation is obtained by a bi-level shifted-window processing algorithm that uses new generalized cooccurrence matrices. The results of each channel, based on individual segmentations, are then analyzed using heuristic rules to obtain the final color and texture based segmentation. The extracted regions are then described through a multilayered neural net for a model-based classification for predicting malignancy.

Original languageEnglish (US)
Title of host publicationBiomedical Engineering Perspectives
Subtitle of host publicationHealth Care Technologies for the 1990's and Beyond
PublisherPubl by IEEE
Number of pages2
Editionpt 3
ISBN (Print)0879425598
StatePublished - 1990
Externally publishedYes
EventProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Philadelphia, PA, USA
Duration: Nov 1 1990Nov 4 1990

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 3
ISSN (Print)0589-1019


OtherProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityPhiladelphia, PA, USA

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics


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