The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Segmentation of digitized dermatoscopic images by two-dimensional color clustering
Open accessAbstract
In this paper a color-based segmentation scheme applied to dermatoscopic images is proposed. The RGB image is processed in the L* u* v* color space. A two-dimensional (2-D) histogram is computed with the two principal components and then smoothed with a Gaussian low-pass filter. The maxima location and a set of features are computed from the histogram contour lines. These features are the number of enclosed pixels, the surface of the base, and the height of the maximum. They allow for the selection of valid clusters which determine the number of classes. The image is then segmented using a modified version of the fuzzy c-means (FCM) clustering technique that takes into account the cluster orientation. Finally, the segmented image is cleaned using mathematical morphology, the region borders are smoothed, and small components are removed.
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Cites
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Nonlinear anisotropic filtering of MRI data
Gerig, G., Kubler, O., Kikinis, R., & Jolesz, F. A. (1992) · IEEE Transactions on Medical Imaging · doi:10.1109/42.141646 · Cited by 1,149
Pattern Recognition: Statistical, Structural and Neural Approaches
Schalkoff, R. J. (1991) · Medical Entomology and Zoology · Cited by 964
On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques
Lim, Y. W., & Lee, S. U. (1990) · Pattern Recognition · doi:10.1016/0031-3203(90)90103-r · Cited by 494
Binder, M. (1995) · Archives of Dermatology · doi:10.1001/archderm.131.3.286 · Cited by 428
Binder, M. (1995) · Archives of Dermatology · doi:10.1001/archderm.1995.01690150050011 · Cited by 354
Stolz, W. (2002) · Cited by 218
Diagnostic Reliability of Dermoscopic Criteria for Detecting Malignant Melanoma
Soyer, H. P., Smolle, J., Leitinger, G., Rieger, E., & Kerl, H. (2009) · Dermatology · doi:10.1159/000246629 · Cited by 117
Automatic color segmentation algorithms-with application to skin tumor feature identification
Umbaugh, S. E., Moss, R. H., Stoecker, W. V., & Hance, G. A. (1993) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/51.232346 · Cited by 87
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Cited by
Comparison of Segmentation Methods for Melanoma Diagnosis in Dermoscopy Images
Silveira, M., Nascimento, J. C., Marques, J. S., Marcal, A. R. S., Mendonca, T., Yamauchi, S., Maeda, J., & Rozeira, J. (2009) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2008.2011119 · Cited by 409
Hashmani, M. A., Jameel, S. M., Rizvi, S. S. H., & Shukla, S. (2021) · Applied Sciences · doi:10.3390/app11052145 · Cited by 53
Metadata
- Authors
- Schmid, P.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 1999
- Volume
- 18
- Issue
- 2
- Pages
- 164-171
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2116930734
- Cited by
- 285
- References
- 13
- FWCI
- 5.99
- Type
- journal article
- Language
- en
- Open access
- green
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