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Research has shown that over 90% of all adults experience dental caries, and the early diagnosis of the carious lesion has become an important aspect of maintaining dental health. Advanced diagnostic and imaging devices can be used to identify tooth damage due to caries, compensating for the low sensitivity (high false negative) rate of visual and visual-tactile inspection by dentists. However, existing systems have such a high false positive rate that dentists often do not rely on the results, instead relying on traditional visual or visual-tactile inspection. Of the existing computer-aided diagnostic systems, few if any use digital image analysis for detection and diagnosis. By using digital images and a graphical user interface, our system will give both quantitative and qualitative feedback to dental practitioners, which will address the weaknesses of existing systems. This paper details our proposed system that makes use of commercial imaging equipment commonly owned by dental practices, including an intraoral camera, to process the digital images of teeth and quantitatively assess the presence and extent of caries on the surface of teeth. We demonstrate the feasibility of using advanced image processing techniques and a C4.5 decision tree classifier to accurately identify caries from digital images.