• International Journal of CAD/CAM
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• v.3 no.1_2
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• pp.97-109
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• 2003

A large scale polygon models are often used to approximately represent 3D CAD models in Digital Engineering environment such as DMU (Digital Mockups) and network based collaborative design. However, they are not suitable for distribution on the network and for interactive rendering. We introduce a new coding system based on subdivision schemes called S-CODE system. In this system, it is possible to highly compress the model with sufficient accuracy and to view the model efficiently in a level of detail (LOD) fashion. The method is based on subdivision surface fitting by which a subdivision surface and curves which approximate a face of a CAD model are generated. We also apply a subdivision method to analytic surfaces such as conical and cylindrical surfaces. A prototype system is developed and used for evaluation with reasonably complicated data. The results show that the method is useful as a CAD data coding system.

• Journal of IKEEE
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• v.16 no.4
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• pp.356-363
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• 2012

Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and traffic sign recognition is one of them. It can provide important information for safety driving. In this paper, we propose a method for traffic sign detection and identification concentrating on reducing the computation time. First, potential traffic signs are segmented by color threshold, and a polygon approximation algorithm is used to detect appropriate polygons. The potential signs are compared with the template signs in the database using SURF and ORB feature matching method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.15-26
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• 2012

Recently, due to applicability increase of vector data based digital map for geographic information and evolution of geographic measurement techniques, large volumed GIS(geographic information service) services having high resolution and large volumed data are flowing actively. This paper proposed an efficient vector map compression technique using the SEC(spatial energy compaction) based on classified bins for the vector map having 1cm detail and hugh range. We encoded polygon and polyline that are the main objects to express geographic information in the vector map. First, we classified 3 types of bins and allocated the number of bits for each bin using adjacencies among the objects. and then about each classified bin, energy compaction and or pre-defined VLC(variable length coding) were performed according to characteristics of classified bins. Finally, for same target map, while a vector simplification algorithm had about 13%, compression ratio in 1m resolution we confirmed our method having more than 80% encoding efficiencies about original vector map in the 1cm resolution. Also it has not only higher compression ratio but also faster computing speed than present SEC based compression algorithm through experimental results. Moreover, our algorithm presented much more high performances about accuracy and computing power than vector approximation algorithm on same data volume sizes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.35-45
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• 2000

The vertex-based boundary encoding scheme is widely used in object-based video coding area and computer graphics due to its scalability with natural looking approximation. Existing single framebased vertex encoding algorithm is not efficient for temporally correlated video sequences because it does not remove temporal redundancy. In the proposed method, a vertex point is selected from not only the boundary points of the current frame but also the vertex points of the previous frame to remove temporal redundancy of shape information in video sequences. The problem of selecting optimal vertex points is modeled as finding shortest path in the directed acyclic graph with weight The boundary is approximated by a polygon which can be encoded with the smallest number of bits for maximum distortion. The temporal redundancy between two successive frames is efficiently removed with the proposed scheme, resulting in lower bit-rate than the conventional algorithms.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.362-371
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• 2003

In this paper, we propose an optimal interest point extraction method to support shape-base image classification and indexing for image database by applying a dynamic threshold that reflects the characteristics of the shape contour. The threshold is determined dynamically by comparing the contour length ratio of the original shape and the approximated polygon while the algorithm is running. Because our algorithm considers the characteristics of the shape contour, it can minimize the number of interest points. For n points of the contour, the proposed algorithm has O(nlogn) computational cost on an average to extract the number of m optimal interest points. Experiments were performed on the 70 synthetic shapes of 7 different contour types and 1100 fish shapes. It shows the average optimization ratio up to 0.92 and has 14% improvement, compared to the fixed threshold method. The shape features extracted from our proposed method can be used for shape-based image classification, indexing, and similarity search via normalization.