Motif analysis for automatic segmentation of CT surface contours into individual surface features

Abstract

This paper presents a new layer-based technique for automatic high-level segmentation of 3-D surface contours into individual surface features through motif analysis. The procedure starts from a contour-based surface model representing a composite surface area of an object. For each of the surface contours, a relative turning angle (RTA) map is derived. The RTA map usually contains noise and minor features. Algorithms based on motif analysis are applied for extracting a main profile of the RTA map free from background noise and other minor features. All feature points on the extracted profile are further identified from the extracted main profile through further motif analysis. The original contour is thus partitioned into individual segments with the identified feature points. A collection of consecutive contour segments among different layers form an individual 3-D surface feature of the original composite surface. The developed approach using motif analysis is particularly useful for the identification of smooth joins between individual surface features and for the elimination of superposed noise and unwanted minor features.