Lip segmentation based on Lambertian shadings and morphological operators for hyper-spectral images

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• 作者：Alessandro Danielis^a ; ^{alessandro.danielis@isti.cnr.it} ; ^{danielis.alessandro@gmail.com}Author Vitae ; Daniela Giorgi^aAuthor Vitae ; Marcus Larsson^bAuthor Vitae ; Tomas Strö ; mberg^bAuthor Vitae ; Sara Colantonio^aAuthor Vitae ; Ovidio Salvetti^aAuthor Vitae
• 关键词：Lip spatial pattern ; Segmentation ; Blood concentration map ; Hyper-spectral ; Lambertian shading ; Morphological ; Fourier descriptors
• 刊名：Pattern Recognition
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：63
• 期：Complete
• 页码：355-370
• 全文大小：2284 K
• 卷排序：63

文摘

We propose an automatic lip segmentation method for hyper-spectral images using a blood concentration map as input data. We generate a subset of Lambertian shaded maps per input image as a pre-processing step to enhance the lip spatial pattern. We perform morphological reconstructions under texture constraints for locating the lip region in each subset. We use Fourier descriptors to model reconstructed and shaded lip boundaries and to extract the segmented candidate. The experiments have been conducted on hyper-spectral images from a private and a public datasets.