Abstract
Melanoma diagnosis in early stages is a difficult task, which requires highly qualified and trained staff. Therefore, a computer aided diagnosis tool to assist non-specialized physicians in the assessment of pigmented lesions would be desirable. In this paper a method to detect streaks, globules and pigment network, which are very important features to evaluate the malignancy of a lesion, is presented. The algorithm calculates the texton histograms of color and texture features extracted from a filter bank, that feed a Support Vector Machine. The method has been tested with 176 images attaining an accuracy of 80%, outperfoming the benchmark techniques used as comparison.
This work have been funded by Junta de Andalucía, Spain, Project no. P11-TIC-7727.
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Jiménez, A., Serrano, C., Acha, B. (2017). Automatic Detection of Globules, Streaks and Pigment Network Based on Texture and Color Analysis in Dermoscopic Images. In: Karray, F., Campilho, A., Cheriet, F. (eds) Image Analysis and Recognition. ICIAR 2017. Lecture Notes in Computer Science(), vol 10317. Springer, Cham. https://doi.org/10.1007/978-3-319-59876-5_54
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