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Labial teeth and gingiva color image segmentation for gingival health-state assessment

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Gingival health state assessment has always been considered of great importance in the field of dentistry. A major concern in this area is the subjectivity that commonly applied assessment methods inherit. Most of the previous approaches that aim at introducing objectivity in the assessment are based on data from photographic images of the gingival area. Nevertheless, they generally lack applicability in the clinical environment because of the requirement of expertise in image processing to perform the analysis. In this work, an enhanced teeth region segmentation scheme is proposed, based on the Self-Organizing Map algorithm. The segmentation task is the basis for further objective assessment of gingival health that can entirely be performed automatically. By introducing a novel training image selection approach, the segmentation performance of this task was increased significantly, compared to previous work. Apart from that, a newly developed spatial segmentation feature in addition to color is investigated and evaluated. The novel Labial Teeth and Gingiva Image Database of the University of Granada is used as benchmark for the segmentation scheme.
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Document Type: Research Article

Publication date: January 1, 2012

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  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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