Volume visualization is an ever-growing field of computer graphics with multiple applications in therepresentation and analysis of 3D scalar data. Such data often comes with a high degree ofcomplexity, making it a challenging task to render a proper 2D image which highlights relevantinformation while discarding other less significant data. In this paper, we present techniques for therendering, identification and representation of various features which are meaningful to the humanvision system, such as contours, outlines or various surface shapes. We use several approaches,based on the orientation of gradient vectors or on image processing techniques, and show how theycan be successfully employed to highlight relevant details from volume data. We illustrate thedifferences between images obtained through 3D rendering directly and those subjected to contourand feature identification techniques and show how these provide a better visual understanding ofthe underlying data.
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