JACIII Vol.20 No.6 pp. 1013-1017
doi: 10.20965/jaciii.2016.p1013

Short Paper:

Extraction and Classification of the Cultural Relic Model Based on Local Geometric Features

Jilai Zhou*, Mingquan Zhou*,**, Guohua Geng*, and Xiaofeng Wang*

*School of Information Science and Technology, Northwest University
Tai Bai Bei Lu No.229, Xi’an, Shaanxi 710069, China

**College of Information Science and Technology, Beijing Normal University
Hai Dian Qu Xin Jie Kou No.19, Beijing 100875, China

April 12, 2016
September 29, 2016
November 20, 2016
feature extract, curvature, cultural relic, local feature, surface type distribution
This paper proposes a novel approach to extracting local geometric features of the cultural relic. We first calculate Gaussian and mean curvature of the model. Then the surfaces of model are labeled for three fundamental types by the value of Gaussian and mean curvature. We use the region growing and expanding search method to obtain the local features of the model. We construct the templates based on the local features and prior knowledge. Finally, we achieve the retrieval of cultural relics by comparing the similarity of the template and the local feature of the model. We apply our method to identify and classify on Terracotta Warriors fragments. Experiments show that our method has the good retrieval performance.
Cite this article as:
J. Zhou, M. Zhou, G. Geng, and X. Wang, “Extraction and Classification of the Cultural Relic Model Based on Local Geometric Features,” J. Adv. Comput. Intell. Intell. Inform., Vol.20 No.6, pp. 1013-1017, 2016.
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