DocumentCode :
109488
Title :
Multiregion Segmentation Based on Compact Shape Prior
Author :
Ran Fan ; Xiaogang Jin ; Wang, Charlie C. L.
Author_Institution :
State Key Lab. of CAD&CG, Zhejiang Univ., Hangzhou, China
Volume :
12
Issue :
3
fYear :
2015
fDate :
Jul-15
Firstpage :
1047
Lastpage :
1058
Abstract :
To solve the problem of generating segmentations of meaningful parts from scanned models with freeform surfaces, we explore a compact shape prior-based segmentation approach in this paper. Our approach is inspired by an observation that a variety of natural objects consist of meaningful components in the form of compact shape and these components with compact shape are usually separated with each other by salient features. The segmentation for multiregions is performed in two phases in our framework. First, the segmentation is taken in low-level with the help of discrete Morse complex enhanced by anisotropic filtering. Second, we extract components with compact shape by using agglomerative clustering to optimize the normalized cut metric, in which the affinities of boundary compatibility, 2D shape compactness and 3D shape compactness are incorporated. The practical functionality of our approach is proved by applying it to the application of customized dental treatment. Note to Practitioners-The research work presented in this paper is to support the procedure of customized design and manufacturing. As a very important preprocessing step for the industrial design of many applications, the 3D shape of real objects must be scanned and reconstructed in computer systems. To assign semantic information to the reconstructed mesh surface, the surface are segmented into meaningful components which, however, is not a well-defined problem. There is no general segmentation approach that has good performance for scanned models with freeform surfaces. According to the observation that models in many industrial applications (e.g., customized dental treatment) have meaningful components in the form of compact shape (e.g., teeth) separating from other regions (e.g., gum), a segmentation method is developed in this paper by using the compact shape prior. The techniques developed here can speedup the design and manufacturing of devices for customized dental treatment (e.g., orthodont- c braces).
Keywords :
filtering theory; image segmentation; pattern clustering; agglomerative clustering; anisotropic filtering; boundary compatibility; compact shape prior; customized dental treatment; discrete Morse complex; freeform surface; multiregion segmentation; normalized cut metric; segmentation generation; Computational modeling; Dentistry; Feature extraction; Measurement; Shape; Teeth; Three-dimensional displays; Anisotropic filtering; compact shape prior; discrete Morse theory; mesh segmentation; normalized metric;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2014.2317497
Filename :
6811228
Link To Document :
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