Duck Hoon Kim

A new shape decomposition scheme for graph-based representation

Nowadays, the part-based representation of a given shape plays a significant role in shape-related applications, such as those involving content-based retrieval, object recognition, and so on. In this paper, to represent both 2-D and 3-D shapes as a relational structure, i.e. a graph, a new shape decomposition scheme, which recursively performs constrained morphological decomposition (CMD), is proposed. The CMD method adopts the use of the opening operation with the ball-shaped structuring element, and weighted convexity to select the optimal decomposition. For the sake of providing a compact representation, the merging criterion is applied using the weighted convexity difference. Therefore, the proposed scheme uses the split-and-merge approach. Finally, we present experimental results for various, modified 2-D shapes, as well as 3-D shapes represented by triangular meshes. Based on the experimental results, it is believed that the decomposition of a given shape coincides with that based on human insight for both 2-D and 3-D shapes, and also provides robustness to scaling, rotation, noise, shape deformation, and occlusion.

Fingerprint Matching Method Using Minutiae Clustering and Warping

Solving non-linear distortion problems in fingerprint matching is important and still remains as a challenging topic. We have developed a new fingerprint matching method to deal with non-linear distortion problems efficiently by clustering locally matched minutiae and warping the fingerprint surface using minutiae clusters. Specifically, local invariant structures encoding the neighborhood information of each minutia are utilized in clustering the matched minutiae and then the fingerprint surface is warped to describe the deformation pattern properly. Finally, to make an additional increase in performance, the overlapped region of two fingerprints is considered in the score computation stage. Experimental results show that the proposed algorithm is performed best compared with other ones

A new attributed relational graph matching algorithm using the nested structure of earth mover's distance

In general, object features can be represented as the nodes in attributed relational graph (ARG) with the connecting edges implying their relations. Therefore, the ARG matching plays a significant role in object recognition. Actually, the ARG matching can be implemented as a 2-step procedure, composed of constructing a distance matrix and establishing the correspondence based on the distance matrix, which seems to be similar to the point matching procedure. In this paper, we present a new ARG matching algorithm using the nested structure of earth movers distance (EMD). More specifically, the nested structure of the EMD consists of inner EMD and outer EMD: The inner EMD reflects the difference of both nodes and edges between a pair of nodes in two ARGs in a perceptual manner, and the outer EMD establishes the correspondence between nodes in the two ARGs in a natural way. In order to demonstrate the robustness of the proposed algorithm against noise, we have conducted synthetic experiments for fully connected and undirected ARGs.

A new MPEG-7 standard: perceptual 3-D shape descriptor

In this paper, we introduce the perceptual 3-D shape descriptor (P3DS) for 3-D object, which has been proposed and adopted as an MPEG-7 standard recently. The descriptor is used as an abstract representation of 3-D object in content-based shape retrieval system. Unlike the conventional descriptors, the P3DS descriptor supports the functionalities like Query by Sketch and Query by Editing which are very useful in real retrieval system. Given a couple of the descriptors, a matching technique is also developed to measure the similarity between them. High retrieval score has been observed when the developed descriptor and the matching technique are used in the retrieval system with the MPEG test database.

A comparative study on attributed relational gra matching algorithms for perceptual 3-D shape descriptor in MPEG-7

Nowadays, the demand on user-friendly querying interface such as query-by-sketch and query-by-editing is an important issue in the content-based retrieval system for 3-D object database. Especially in MPEG-7, P3DS (Perceptual 3-D Shape) descriptor has been developed in order to provide the user-friendly querying, which can not be covered by an existing international standard for description and browsing of 3-D object database. Since the P3DS descriptor is based on the part-based representation of 3-D object, it is a kind of attributed relational gra (ARG) so that the ARG matching algorithm naturally follows as the core procedure for the similarity matching of the P3DS descriptor. In this paper, given a P3DS database from the corresponding 3-D object database, we bring focus into investigating the pros and cons of the target ARG matching algorithms. In order to demonstrate the objective evidence of our conclusion, we have conducted the experiments based on the database of 480 3-D objects with 33 categories in terms of the bulls eye performance, average normalized modified retrieval rate, and <i>precision/recall</i> curve.

A new 3-D model retrieval system based on aspect-transition descriptor

In this paper, we propose a new 3-D model retrieval system using the Aspect-Transition Descriptor which is based on the aspect graph representation [1,2] approach. The proposed method differs from the conventional aspect graph representation in that we utilize transitions as well as aspects. The process of generating the Aspect-Transition Descriptor is as follows: First, uniformly sampled views of a 3-D model are separated into a stable and an unstable view sets according to the local variation of their 2-D shape. Next, adjacent stable views and unstable views are grouped into clusters and we select the characteristic aspects and transitions by finding the representative view from each cluster. The 2-D descriptors of the selected characteristic aspects and transitions are concatenated to form the 3-D descriptor. Matching the Aspect-Transition Descriptors is done using a modified Hausdorff distance. To evaluate the proposed 3-D descriptor, we have evaluated the retrieval performance on the Princeton benchmark database [3] and found that our method outperforms other retrieval techniques.

How CanWe Evaluate Object Recognition Algorithms Using a Public Object Image Database

In this paper, to evaluate the performance of object recognition algorithms, we propose a new evaluation framework by synthesizing natural scenes based on the Amsterdam Library of Object Images [1]. Here, the evaluation of an object recognition algorithm has the basis on searching an object in a synthetic scene. More specifically, an object is selected, and then the synthetic scene under a specific condition is generated by using images, affected by that condition, of that object and other objects in the database. When generating the synthetic scene, the other objects are randomly selected and all objects are naturally distributed in the synthetic scene. Let us refer to this synthetic scene as a Virtual Scene. Then the performance of object recognition algorithms for the specific condition can be analyzed by using a group of Virtual Scenes in that condition. As an example of utilizing the proposed framework, an object recognition algorithm using the scale-invariant feature transform [2] has been evaluated and analyzed in the case of changing the viewing direction, illumination color, and illumination direction.

Interactive 3-D Shape Retrieval System Using the Attributed Relational Graph

One of the issues in 3-D shape retrieval arises from the fact that users suffer inherent difficulty in generating a 3-D query. Therefore, the demands on the user-friendly querying interface such as query by sketch and query by editing are increasing. In this paper, we propose a new shape retrieval system using the attributed relational graph (ARG) composed of nodes with unary attributes and edges with binary relations for interactive searching and comparing 3-D objects. As similar to other systems, the ARG-based retrieval system consists of two components: the ARG generation via feature extraction and its similarity matching. For the ARG generation, we adopt a morphological shape decomposition scheme as a part-based representation. More specifically, the part-based representation can be generated from the decomposition result and encoded into the ARG. In the case of similarity matching, we consider various ARG matching algorithms such as earth movers distance, spectral analysis, relaxation and modified nested earth movers distance. Finally, we have conducted the experiments for the ARG with various matching algorithms and the Shape3D, i.e.an international standard for description and browsing of 3-D object database in MPEG-7, using the database of 480 3-D objects with 33 categories in terms of the bulls eye performance, the average normalized modified retrieval rate, and the precision/recall curve.

Graph representation by medial axis transform for 3D image retrieval

Recently, the interests in the 3D image, generated from the range data and CAD, have exceedingly increased, accordingly a various 3D image database is being constructed. The efficient and fast scheme to access the desired image data is the important issue in the application area of the Internet and digital library. However, it is difficult to manage the 3D image database because of its huge size. Therefore, a proper descriptor is necessary to manage the data efficiently, including the content-based search. In this paper, the proposed shape descriptor is based on the voxelization of the 3D image. The medial axis transform, stemming from the mathematical morphology, is performed on the voxelized 3D image and the graph, which is composed of nodes and edges, is generated from skeletons. The generated graph is adequate to the novel shape descriptor due to no loss of geometric information and the similarity of the insight of the human. Therefore the proposed shape descriptor would be useful for the recognition of 3D object, compression, and content-based search.

Regular polyhedral descriptor for 3-D object retrieval system

Recently, the 3-D object retrieval system attempts to integrate 2-D visual descriptors since some applications including e-shopping cannot employ 3-D object as a query. For an example, the multiple views have been developed in MPEG-7, but it cannot consider the spatial distribution of 3-D object and has heavy computational complexity because of the matching procedure in a combinatorial manner. In this paper, a novel descriptor for the 3-D object retrieval system, the regular polyhedral descriptor or regular polyhedron, is proposed. The proposed descriptor, which consists of the selection of equally distributed view positions and matching strategy using the regular polyhedron, is based on the multiple view, but it can improve the multiple view by using the property of the regular polyhedron. Experimental results show that the proposed descriptor has the retrieval performance comparable to the multiple views, in terms of the bulls eye performance (BEP) and average normalized modified retrieval rate (ANMRR).