• 한국정보전자통신기술학회논문지
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• 제10권2호
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• pp.147-153
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• 2017

텍스쳐를 효과적으로 표현하는 것은 컴퓨터 비전 분야에서 매우 중요한 과정이다. 효과적인 텍스쳐 표현을 통해 텍스쳐 분류나 텍스쳐 분할 등의 처리 성능을 향상시킬 수 있다. 가버 필터는 텍스쳐 표현을 위해 오랫동안 사용된 다해상도 스케일 기반의 방법이다. 가버 필터는 텍스쳐 분류나 분할에 높은 성능을 제공한다. 그러나 처리 과정의 연산량으로 인해 처리 시간이 매우 많이 소요되어 실제 응용에서는 사용하기 어려운 문제가 있다. 본 논문에서는 가버 필터와 유사하게 다해상도 스케일 기반으로 텍스쳐를 표현할 수 있는 새로운 특징 표현 방법을 제안한다. 제안한 방법은 주파수 공간에서 방향과 스케일을 기반으로 다해상도 스케일 기반으로 텍스쳐를 표현한다. 2가지 실험 영상 집합에 대해 분류 실험을 수행하여 제안한 특징의 유용성을 확인하였다. 가버 필터와 유사한 분류 성능을 제공하면서 처리 속도는 가버 필터의 5%이하로 줄일 수 있는 것을 확인하였다.

• 한국멀티미디어학회논문지
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• 제13권2호
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• pp.237-248
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• 2010

컴퓨터/로봇 비전 분야에서 실세계 장면들을 촬영할 때, 상당 부분의 텍스처 기반 패턴들이 발견되는데, 본 논문에서는 그런 다양한 패턴들을 적절하게 표현할 수 있는 수학적 모델(Gabor 함수)을 기반으로 한 특징 측정 좌표 체계를 소개한다. 그 체계를 통한 텍스처 패턴의 여러 특징들에 대한 측정값의 표현은 텍스처 패턴분류 작업을 수행하는데 보다 효율적인 성능을 가능케 한다. 또한 실험에 사용된 텍스처 이미지 데이터의 좌표 체계에서의 표현 정보가 추후 유사 연구들에 의해 활용될 수 있으며, 제안된 좌표 체계에서 표현된 패턴 데이터를 분류하는데 가장 적합한 의사결정나무 알고리듬을 사용한다. 최종적으로, 다양한 텍스처 패턴분류 실험을 통해 기존 연구 방법들에 비해 연구 결과의 개선이 있음을 보여준다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 Proceedings International Workshop on New Video Media Technology
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• pp.29-34
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• 1996

This paper proposes a new concept in video called Graphical Video. Graphical Video is a content-based and scalable video representation. A video consists of several elements such as moving images, still images, graphics, characters and charts. All of these elements can be represented graphically except moving images. It is desirable to transform these moving images graphical elements so that they can be treated in the same way as other graphical elements. To achieve this, we propose a new graphical representation of moving images using spatio-temporal clusters, which consist of texture and contours. The texture is described by three-dimensional fractal coefficients, while the contours are described by polygons. We propose a method that gives domain pool location and size as a means to describe cluster texture within or near a region of clusters. Results of an experiment on texture quality confirm that the method provides sufficiently high SNR as compared to that in the original three-dimensional fractal approximation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.402-410
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• 2017

For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권1호
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• 한국정보통신학회논문지
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• 제6권4호
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• pp.645-651
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• 2002

본 논문에서는 전체적으로 묘사된 얼굴의 특징을 이용하여 얼굴 영상을 합성하는 방법을 제안한다. 제안된 방법은 얼굴의 형태를 대조하는 방법을 이용하여 만든 원영상의 작은 부분 영상들을 가지고 얼굴을 재현하였으며 얼굴 영상에서 2차원적 형태와 구조를 분리함으로서 음영부분과 경계부분을 표현할 수 있었으며, 영상과 영상의 특성을 나타내는 얼굴 부분영역을 조화롭게 재배치함으로서 합성을 가능케 하였다. 실험결과 본 논문에서 제안된 방법으로 합성한 얼굴 영상은 항상 자연스러운 얼굴 영상을 나타냄으로서 제안된 방법의 실효성을 입증하였다.

• ETRI Journal
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• 제44권1호
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• pp.51-61
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• 2022

In this paper, we introduced a novel voxel-wise UV parameterization and view-dependent texture synthesis for the immersive rendering of a truncated signed distance field (TSDF) scene model. The proposed UV parameterization delegates a precomputed UV map to each voxel using the UV map lookup table and consequently, enabling efficient and high-quality texture mapping without a complex process. By leveraging the convenient UV parameterization, our view-dependent texture synthesis method extracts a set of local texture maps for each voxel from the multiview color images and separates them into a single view-independent diffuse map and a set of weight coefficients for an orthogonal specular map basis. Furthermore, the view-dependent specular maps for an arbitrary view are estimated by combining the specular weights of each source view using the location of the arbitrary and source viewpoints to generate the view-dependent textures for arbitrary views. The experimental results demonstrate that the proposed method effectively synthesizes texture for an arbitrary view, thereby enabling the visualization of view-dependent effects, such as specularity and mirror reflection.

• 한국정보전자통신기술학회논문지
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• 제3권3호
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• pp.39-44
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• 2010

본 연구에서는 벡터 변환 기법을 이용하여 연령변화에 따른 얼굴변환 기법을 제안 하였다. 제안한 기법은 주관성을 배제하고 일관성과 신뢰성을 높이기 위하여 모핑과 벡터 모델을 적용하였다. 또한, 형태에 따른 질감변화 요인을 정의하고 내부 외부 환경 변화에 대한 형태 변환 요소를 고려하였다. 제안한 방법의 타당성을 확인하기 위하여 실험결과를 정성적인 방법으로 유사성 평가를 수행하였는 바, 14세부터 60세까지의 얼굴 변환 결과가 매우 유사하게 평가 되었다.