Objective
One of the major Challenges in dentistry is the correct selection of tooth color as close to the natural adjacent tooth color as possible so this study was directed to development alternative way to traditional methods for shade matching.
The purpose of this study is to develop, implement and evaluate a smartphone application that depends on K-nearest neighbor classification algorithms for proper shade matching to come to the aid of dentists and largely to remove the inherent subjectivity of the human sight.
Subjects and Methods
A total of 1300 shade tab images (50 per shade tab) were captured using a smartphone main camera with auto-mode settings and special ring light which emits 5500 k light temperature. The images were shot at angled distances of 14–20 cm from a shade guide. Color features were extracted and classification using KNN classification algorithm to act as software dataset.50 upper central incisors were captured by smartphone and the shade of these teeth were matched using developed software and, visual methods compere to spectrophotometer.