DENTAL IMAGE SEGMENTATION BASED ON MULTIPLE LINEAR REGRESSION CORRELATES WITH NORMALIZED RGB VALUES

摘要

This paper presented an approach for segmenting dentalrntooth images based on multiple linear regression correlatesrnwith normalized RGB values, which provides preparatoryrnwork to form a complete progress for dental plaque quantification.rnThe approachwas applied to clinical dental toothrnimages. The experimental results showed that this methodrnprovided objective, and time-saving segmentations comparedrnwith those of traditional multiple linear regressionrncorrelates with RGB values. Dilation and erosion techniquesrnare used to increase the efficacy of the dental toothrnimage processing.