Template-matching approach to edge detection of volume data

This paper proposes a template-matching approach to the edge detection of volume data. Twenty-six templates of an ideal step-like edge in the 3×3×3 neighborhood of volume data are given, and the step-like edge of volume data is detected by matching such patterns in various orientations. The approach is a simple and straightforward one for edge detection of volume data. It generalizes the well-known Kirsch operator for 2D images. It can detect change of intensity in every direction, and has the property of rotation invariance in 18-neighborhood. Implementation of proposed approach is given for biological and medical volume data, including MRI and CT volume data