Quantification of Pigmented Regions in Detracted Images

This study presents a method for analyzing and quantifying pigmented areas on dental surfaces after the application of caries detection products. The methodology integrates image enhancement, the creation of binary masks, and conversion to the HSV color space to isolate and accurately calculate the extent of pigmentation. A dataset consisting of 200 images of unpigmented teeth and 200 images of pigmented teeth was used, with strict criteria for selecting images that provided a clear frontal view, focusing on the upper and lower canine regions. The image processing steps included using LabelMe software for manual annotation and applying binary masks to segment the teeth from the background. Specific color filters identified pigmented regions. Histogram analysis in the HSV space validated the predominance of red shades corresponding to the pigmented areas, confirming the accuracy of the segmentation. The results demonstrate the effectiveness of the proposed method for calculating pigmented areas, providing an objective measure that can be used to assess the efficacy of products designed for bacterial plaque detection in dental applications.

Authors

Publication Details

Journal
Journal of Bioengineering, Technologies and Health
Published
2025-02-21
DOI
https://doi.org/10.34178/jbth.v7isuppl1.435
Primary Topic
Image Processing Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Quantification of Pigmented Regions in Detracted Images

Marcos Batista Figueredo, Eugênio Rocha da Silva Júnior, Uanderson Lima Santos
Journal of Bioengineering, Technologies and Health
Image Processing Techniques and Applications
article

Quantification of Pigmented Regions in Detracted Images

Marcos Batista Figueredo, Eugênio Rocha da Silva Júnior, Uanderson Lima Santos
article en

Abstract

This study presents a method for analyzing and quantifying pigmented areas on dental surfaces after the application of caries detection products. The methodology integrates image enhancement, the creation of binary masks, and conversion to the HSV color space to isolate and accurately calculate the extent of pigmentation. A dataset consisting of 200 images of unpigmented teeth and 200 images of pigmented teeth was used, with strict criteria for selecting images that provided a clear frontal view, focusing on the upper and lower canine regions. The image processing steps included using LabelMe software for manual annotation and applying binary masks to segment the teeth from the background. Specific color filters identified pigmented regions. Histogram analysis in the HSV space validated the predominance of red shades corresponding to the pigmented areas, confirming the accuracy of the segmentation. The results demonstrate the effectiveness of the proposed method for calculating pigmented areas, providing an objective measure that can be used to assess the efficacy of products designed for bacterial plaque detection in dental applications.

Journal of Bioengineering, Technologies and HealthVol. 7(Suppl1)
Openalex Percentile: Top 96%
Image Processing Techniques and Applications
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Quantification of Pigmented Regions in Detracted Images — Marcos Batista Figueredo, Eugênio Rocha da Silva Júnior, et al. · Journal of Bioengineering, Technologies and Health (2025) | TGRS Research Map | TGRS