• The Transactions of the Korea Information Processing Society
• /
• v.5 no.11
• /
• pp.2884-2896
• /
• 1998

For on-line signature verification, the local shape of a signature is an important information. The current approaches, in which signatures are represented into a function of time or a feature vector without regarding of local shape, have not used the various features of local shapes, for example, local variation of a signer, local complexity of signature or local difficulty of forger, and etc. In this paper, we propose a new technique for on-line signature verification based on a structural signature representation so as to analyze local shape and to make a selection of important local parts in matching process. That is. based on a structural representation of signature, a technique of important of local weighting and personalized decision threshold is newly introduced and its experimental results under different conditions are compared.

• Korean Journal of Computational Design and Engineering
• /
• v.9 no.1
• /
• pp.51-61
• /
• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes.. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the second one of the two companion papers, describes the similarity assessment method using NFD.

• Korean Journal of Computational Design and Engineering
• /
• v.9 no.1
• /
• pp.44-50
• /
• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the first one of the two companion papers, describes the similarity assessment methods using convex decomposition and FFD.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.10
• /
• pp.194-202
• /
• 1999

A method for pattern recognition based on wavelet transform is proposed in this paper. The boundary of the object to be recognized includes shape information for object of machine parts. The contour is first represented using a one-dimensional signal and normalized about translation, rotation and scale, then is used to build the wavelet transform representation of the object. Wavelets allow us to decompose a function into multi-resolution hierarchy of localized frequency bands. The recognition of 2-dimensional object based on the wavelet is described to analyze the shape of analysis technique; the discrete wavelet transform(DWT). The feature vectors obtained using wavelet analysis is classified using a multi-layer neural network. The results show that, compared with the use of fourier descriptors, recognition using wavelet is more stable and efficient representation. And particularly the performance for objects corrupted with noise is better than that of other method.

• Korean Journal of Computational Design and Engineering
• /
• v.11 no.4
• /
• pp.315-325
• /
• 2006

It is very often necessary to search for similar parts during designing a new product because its parts are often easily designed by modifying existing similar parts. In this way, the design time and cost can be reduced. Thus it would be nice to have an efficient similarity comparison algorithm that can be used anytime in the design process. There have been many approaches to compare shape similarity between two solids. In this paper, two parts represented in B-Rep is compared in two steps: one for overall appearances and the other for detail features. In the first step, geometric information is used in low level of detail for easy and fast pre-classification by the overall appearance. In the second step, feature information is used to compare the detail shape in high level of detail to find more similar design. To realize the idea above, a multi resolution algorithm is proposed so that a given solid is described by an overall appearance in a low resolution and by detail features in high resolution. Using this multi-resolution representation, parts can be compared based on the overall appearance first so that the number of parts to be compared in high resolution is reduced, and then detail features are investigated to retrieve the most similar part. In this way, computational time can be reduced by the fast classification in the first step while reliability can be preserved by detail comparison in the second step.

• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.4
• /
• pp.262-268
• /
• 2017

Intelligent video surveillance systems have been developed to monitor global areas and find specific target objects using a large-scale database. However, person re-identification presents some challenges, such as pose change and occlusions. To solve the problems, this paper presents an improved person re-identification method using sparse representation and saliency-based dictionary construction. The proposed method consists of three parts: i) feature description based on salient colors and textures for dictionary elements, ii) orthogonal atom selection using cosine similarity to deal with pose and viewpoint change, and iii) measurement of reconstruction error to rank the gallery corresponding a probe object. The proposed method provides good performance, since robust descriptors used as a dictionary atom are generated by weighting some salient features, and dictionary atoms are selected by reducing excessive redundancy causing low accuracy. Therefore, the proposed method can be applied in a large scale-database surveillance system to search for a specific object.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.5
• /
• pp.836-858
• /
• 2010

Web Services allow a user to integrate applications from different platforms and languages. Since mobile applications often run on heterogeneous platforms and conditions, Web Service becomes a popular solution for integrating with server applications. However, because of its verbosity, XML based SOAP messaging gives the possible overhead to the less powerful mobile devices. Based on the mobile client's behavior that it usually exchanges messages with Web Service continuously in a session, we design the Handheld Flexible Representation architecture. Our proposed architecture consists of three main components: optimizing message representation by using a data format language (Simple_DFDL), streaming communication channel to reduce latency and the Context-store to store context information of a session as well as redundant parts of the messages. In this paper, we focus on the Context-store and describe the architecture with the Context-store for improving the performance of mobile Web Service messaging. We verify our approach by conducting various evaluations and investigate the performance and scalability of the proposed architecture. The empirical results show that we save 40% of transit time between a client and a service by reducing the message size. In contrast to solutions for a single problem such as the compression or binarization, our architecture addresses the problem at a system level. Thus, by using the Context-store, we expect reliable recovery from the fault condition and enhancing interoperability as well as improving the messaging performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.12
• /
• pp.5464-5484
• /
• 2016

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

• Journal of Computational Design and Engineering
• /
• v.2 no.1
• /
• pp.55-66
• /
• 2015

To satisfy safety regulations of Economic Commission for Europe (ECE), the surface regions of automobile parts must have a sufficient degree of roundness if there is any chance that they could contact a sphere of 50.0 mm radius (exterior parts) or 82.5 mm radius (interior parts). In this paper, a new offset-based method is developed to automatically detect the possible sphere-contacting shape of such parts. A polyhedral model that precisely approximates the part shape is given as input, and the offset shape of the model is obtained as the Boolean union of the expanded shapes of all surface triangles. We adopt a triple-dexel representation of the 3D model to enable stable and precise Boolean union computations. To accelerate the dexel operations in these Boolean computations, a new parallel processing method with a pseudo-list structure and axis-aligned bounding box is developed. The possible sphere-contacting shape of the part surface is then extracted from the offset shape as a set of points or a set of polygons.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.6
• /
• pp.132-140
• /
• 2003

In this paper, we propose a new scheme for view-dependent transmission of three-dimensional (3-D) polygonal mesh models with hierarchial partitioning. In order to make a view-dependent representation of 3-D mesh models, we combine sequential and progressive mesh transmission techniques. By setting higher priorities to visible parts than invisible parts, we can obtain good qualify of 3-D models in a limited transmission bandwidth. In this paper, we use a multi -layer representation of 3-D mesh models based on hierarchical partitioning. After representing the 3-D mesh model in a hierarchical tree, we determine resolutions of partitioned submeshes in the last level. Then, we send 3-D model data by view-dependent selection using mesh merging and mesh splitting operations. By the partitioned mesh merging operation, we can reduce the joint boundary information coded redundantly in the partitioned submeshes. We may transmit additional mesh information adaptively through the mesh spritting operation.