• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.50-60
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• 2000

In this paper, we propose a new composite feature consists of both color and shape information that are suitable for the task of character image retrieval. This approach extracts shape-based information using Zernike moments from Y image in YCbCr color space. Zernike moments can extract shape-based features that are invariant to rotation, translation, and scaling. We also extract color-based information from the DCT coefficients of Cr and Cb image. This approach is good method reflecting human visual property and is suitable for web application such as large image database system and animation because higher retrieval rate has been achieved using only 36 features. In experiment, this method is applied to 3,834 character images. We confirmed that this approach brought about excellent effect by ANMRR(Average of Normalized, Modified Retrieval Rank), which is used in the evaluation measure of MPEG-7 color descriptor and BEP(Bull's Eye Performance), which is used in evaluation measure of shape descriptor in character image retrieval.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.737-747
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• 2019

Shape description is an important and fundamental issue in content-based image retrieval (CBIR), and a number of shape description methods have been reported in the literature. For shape description, both global information and local contour variations play important roles. In this paper a new included-angular ternary pattern (IATP) based shape descriptor is proposed for shape image retrieval. For each point on the shape contour, IATP is derived from its neighbor points, and IATP has good properties for shape description. IATP is intrinsically invariant to rotation, translation and scaling. To enhance the description capability, multiscale IATP histogram is presented to describe both local and global information of shape. Then multiscale IATP histogram is combined with included-angular histogram for efficient shape retrieval. In the matching stage, cosine distance is used to measure shape features' similarity. Image retrieval experiments are conducted on the standard MPEG-7 shape database and Swedish leaf database. And the shape image retrieval performance of the proposed method is compared with other shape descriptors using the standard evaluation method. The experimental results of shape retrieval indicate that the proposed method reaches higher precision at the same recall value compared with other description method.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.53-64
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• 2009

This paper presents a performance evaluation of shape descriptors for gait analysis in case of silhouette sequence images. We used moment descriptors(MD), Fourier descriptors(FD) and Zernike descriptors(ZD) as a shape descriptor. To evaluate their performance, we firstly defined the performance index, that is, AI(asymmetry index) and PI(periodic index) based on the periodic property of the gait images. This is why they are represented by periodic parameters due to periodic gait images. This index means that how the shape is represented periodically. According to these indexes, we evaluated the data sets with periodic images, downloaded from internet. The results showed that Zernike descriptors had better performance of AI = 1.09 and PI = 2.21 than others. And in case of FD and ZD, it's efficient to implement the gait analysis with 5~10 parameters.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.10-17
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• 2018

Persistence Betty numbers, which are the rank of the persistent homology, are a generalized version of the size theory widely known as a descriptor for shape analysis. They show robustness to both perturbations of the topological space that represents the object, and perturbations of the function that measures the shape properties of the object. In this paper, we present a shape matching algorithm which is based on the use of persistence Betty numbers. Experimental tests are performed with Kimia dataset to show the effectiveness of the proposed method.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.67-90
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• 2019

Accurate detection, tracking and analysis of human movement using robots and other visual surveillance systems is still a challenge. Efforts are on to make the system robust against constraints such as variation in shape, size, pose and occlusion. Traditional methods of detection used the sliding window approach which involved scanning of various sizes of windows across an image. This paper concentrates on employing a state-of-the-art, hierarchical graph based method for segmentation. It has two stages: part level segmentation for color-consistent segments and object level segmentation for category-consistent regions. The tracking phase is achieved by employing SIFT keypoint descriptor based technique in a combined matching and tracking scheme with validation phase. Localization of human region in each frame is performed by keypoints by casting votes for the center of the human detected region. As it is difficult to avoid incorrect keypoints, a consensus-based framework is used to detect voting behavior. The designed methodology is tested on the video sequences having 3 to 4 persons.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.751-753
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• 2010

본 논문에서는 위상차 현미경 영상 내 U87 세포의 정확한 형태학적 분류를 위한 이진 분류기 구축 방법을 제안한다. 본 방법은 Fourier descriptor 기반 세포형상 표현을 SVM 이진분류기 구축에 사용함으로써 분류 대상인 원추형과 원형세포에 대해 영상 내 세포의 위치와 회전, 크기의 변화에 대해 강인한 분류성능을 제공한다. 본 실험을 통해 polynomial 커널에서 학습된 SVM 분류기가 linear, RBF, sigmoid 에 비교하여 가장 정확한 분류 성능을 보임을 확인하였다. 본 연구는 논문상 기준인 두 종류의 세포 형태 분류기를 기반 프레임워크로 삼아 좀더 다양한 세포 형태를 분류할 수 있도록 개선된다면 악성뇌종양의 전이억제치료에 효과적인 전이행동분석에 도움을 줄 수 있을 것으로 기대된다.

• Journal of the Korean GEO-environmental Society
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• v.18 no.3
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• pp.25-30
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• 2017

This paper introduces a novel method to quantify the morphological evolution of the strain response envelope. The strain response envelope is defined as an image in strain increment space corresponding to the unit stress input in stress space. Based on the shape of strain response envelopes, the deformation characteristics of soils can be described using the framework of elastic-plastic theory. Fourier descriptor analysis was used to investigate the morphological characteristics of strain response envelopes. The numerical results show that when the stress input remains in the initial yield surface the Fourier descriptors remain constant. Once the stress input crosses the initial yield surface, every descriptors deals in this study change. Numerical and experimental results of this study show that clear yielding response is only found in natural block samples. Among the Fourier descriptors, the descriptor called as asymmetry is the best for detecting the yield and is minimally sensitive to the number of input stress paths.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.1
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• pp.133-142
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• 1993

This paper prrsents shape matching of two-dimensional object. This shape matching is applied to two-dimensional simple c10sedcurves represented by polygons. A large number of shape matching procedures have proposed baseed on teh view that shape can be represented by a vector of numerical features, and that this representation can be matched using techniques from statical pattern recognition. The varieties of features that have been extracted from shapes and used to represent them are numerous. But all of these feature-based approches suffer from the shortcoming that the descriptor of a segment of a shape do not ordinarily bear any simple relations hip to the description for the entire shape. We solve the segment matching problem of shape matching, defined as the recognition of a piece of a shape as approximate match to a part of large shape, by using relaxation labeling technique.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.411-419
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• 2013

Research on developing algorithms for building modeling such as extracting outlines of the buildings and segmenting patches of the roofs using aerial images or LiDAR data are active. However, utilizing information from the building model is not well implemented yet. This study aims to propose a scheme for search identical or similar shape of buildings by utilizing graph topology pattern matching under the assumptions: (1) Buildings were modeled beforehand using imagery or LiDAR data, or (2) 3D building data from digital maps are available. Side walls, segmented roofs and footprints were represented as nodes, and relationships among the nodes were defined using graph topology. Topology graph database was generated and pattern matching was performed with buildings of various shapes. The results show that efficiency of the proposed method in terms of reliability of matching and database structure. In addition, flexibility in the search was achieved by altering conditions for the pattern matching. Furthermore, topology graph representation could be used as scale and rotation invariant shape descriptor.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.300-311
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• 2014

According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.