DullRazor
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Recently, there has been an increase in the number of studies using image processing
techniques to analyze melanocytic lesions for atypia and possible malignancy, and for
total-body mole mapping. Such lesions, however, can be partially obscured by body hair;
and, to date, no study has fully addressed the problem of human hair occluding imaged
lesions. In a previous study we designed an automatic segmentation program to
differentiate skin lesions from normal healthy skin. Our program performed well with
most images the exception being images where dark thick hair covers part of the
lesions. Dark hair confused the program which resulted in unsatisfactory segmentation
results.
Presented here is a method to remove hair from images using a pre-processing program
called DullRazor [1]. DullRazor performs the following
steps:
- It identifies the dark hair locations by a generalized grayscale morphological closing
operation,
- It verifies the shape of the hair pixels as thin and long structure, and replace the
verified pixels by a bilinear interpolation, and
- It smooths the replaced hair pixels with an adaptive median filter.
The algorithm has been implemented in C on a SunOS 4.x workstation. (The program can be
run on Sun Solaris workstations as well.) It has been tested on real nevi images with
satisfactory results. Figure 1. shows a lesion covered by thick hair and Figure 2. shows
the result with hair removed. The man.txt
file provides more details.
| Figure 1. |
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Figure 2. |
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We have ported the program to Windows, running under Windows
98/NT/Me/2000/XP.
DullRazor can be downloaded and used without fee for
non-commerical purpose. The full license is included in the download.
Download the Unix version of DullRazor (dullrazor.zip, 87KB): follow this link.
Download the Windows version of DullRazor (dullrazor_wins.zip, 327KB): follow this link.
For more information, please contact Tim Lee, Ph.D.:
E-mail: tlee@bccancer.bc.ca
[1] Lee T, Ng V, Gallagher R, Coldman A, McLean D. DullRazor: A software approach to
hair removal from images. Computers in Biology and Medicine 1997;27:533-543. |