Independent Histogram Pursuit for Segmentation of Skin Lesions

Abstract

In this paper, an unsupervised algorithm, called the Independent Histogram Pursuit (IHP), for segmenting dermatological lesions is proposed. The algorithm estimates a set of linear combinations of image bands that enhance different structures embedded in the image. In particular, the first estimated combination enhances the contrast of the lesion to facilitate its segmentation. Given an N-band image, this first combination corresponds to a line in N dimensions, such that the separation between the two main modes of the histogram obtained by projecting the pixels onto this line, is maximized. The remaining combinations are estimated in a similar way under the constraint of being orthogonal to those already computed. The performance of the algorithm is tested on five different dermatological datasets. The results obtained on these datasets indicate the robustness of the algorithm and its suitability to deal with different types of dermatological lesions. The boundary detection precision using k-means segmentation was close to 97%. The proposed algorithm can be easily combined with the majority of classification algorithms.

Segmentation of Melanoma Skin Lesion Using Perceptual Color Difference Saliency with Morphological Analysis

“…The expression [ ] 0 in (11) and (16) means that " " in radian is to be expressed in degree and the expression [ ] in (13) and (14) indicates that " " in degree is to be expressed in radian. The other symbols appearing in the color difference equation are defined as follows:…”

“…Moreover, segmentation is one of the central stages for computer aided diagnosis of melanoma with dermoscopic images [13]. The automatic segmentation of skin lesion is particularly challenging because of the possible presence of undesirable factors in the form of skin hairs, specular 2 Mathematical Problems in Engineering reflections, variegated coloring, weak edges, low contrast, irregular and fuzzy borders, marker ink, color chart, ruler marks, dark corners, skin lines, blood vessels, and air or oil bubbles [10,[14][15][16].…”

Improved Skin Lesion Diagnostics for General Practice by Computer-Aided Diagnostics

“…A technique, known as Independent Histogram Pursuit [61], consists in finding a combination of spectral bands that enhances the contrast between healthy skin and lesions. Another method used in dermoscopic images consists in determining the optimal weights and converting them by maximizing Otsu's histogram bimodality measure [62,63].…”

“…In order to enhance the edges in the original images and facilitate the segmentation process, it is common to apply the Karhunen-Loève Transform (KLT) in pigmented skin lesions [61,[67][68][69].…”

Practical Imaging in Dermatology

“…The emphasis is often on detecting signs of melanoma and there exists a lot of literature on melanoma segmentation (Celebi et al, 2009;Gomez et al, 2008;2007), but only a few studies of measurement of allergic reactions from 2D pictures (Nischik & Forster, 1997;Roullot et al, 2005). There are also some studies which have been performed with 3D imaging (Santos et al, 2008) or other specialized imaging hardware (Wöhrl et al, 2006).…”