• Journal of International Society for Simulation Surgery
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• 제3권2호
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• pp.46-48
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• 2016

Purpose In face reocognition area, estimating occlusion in face images is on the rise. In this paper, we propose a new face recognition algorithm based on dual sparse representation to solve this problem. Method Each face image is partitioned into several pieces and sparse representation is implemented in each part. Then, some parts that have large sparse concentration index are combined and sparse representation is performed one more time. Each test sample is classified by using the final sparse coefficient where correlation between the test sample and training sample is applied. Results The recognition rate of the proposed algorithm is higher than that of the basic sparse representation classification. Conclusion The proposed method can be applied in real life which needs to identify someone exactly whether the person disguises his face or not.

• 한국의류학회지
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• 제44권3호
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• pp.413-426
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• 2020

This study researches the association between associative vocabulary and fashion image language in order to extract ideas that can be used as basic data for design ideas. Classic - avant-garde imaged language were chosen as theme words and each 70 questionnaires per a final image word were used for analysis. We obtained the following results by researching keywords that explained classic image words through a word cloud technique. It was found to have high central representation in the order of suit, classical, basic, music, Chanel, black and traditional. The core key words explaining avant-garde image language were found to have a central representation in the order of : peculiar, huge, Comme des Garçons, artistic, creative, deconstruction and individuality. We extracted the necessary idea dimensions needed for design ideas through associative network graph analysis. In the case of classical image language, it was named as the Mannish Item, Music, Modern Color, and the Traditional Classicality dimensions. In the case of avant-garde image language, it was named as the Key Image, Artistic Aura, Key Design and Designers dimensions.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• 한국통신학회논문지
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• 제34권2C호
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• pp.186-193
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• 2009

다시점 비디오는 데이터 양이 매우 많아서 이를 효과적으로 저장하고 전송하기 위해서는 새로운 압축 부호화의 기술 개발이 필수적이다. 계층적 깊이 영상은 다시점 비디오를 효과적으로 부호화할 수 있는 방법으로 여러 시점의 컬러와 깊이 영상을 합성하여 하나의 데이터 구조로 만든 것이다. 본 논문에서는 실제 거리비교, 오버랩 문제해결, YCrCb 컬러변환을 이용한 효율적인 계층적 깊이 영상 표현을 통해서 다시점 영상에 대한 압축 효율을 향상시키는 방법을 제안하였다. 실험 결과를 통해서 압축성능 향상과 우수한 복원 성능을 얻을 수 있었다.

• 조형예술학연구
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• 제2권
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• pp.193-221
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• 2000

The postmodern culture since the later 20C breaks downa tradition a relation between the reality and languages or sign images expressing it. It develops in the way to review the meaning on the object's imitation or the representation to have been followed since Plato and represent the new state and concept of expressed things. Also, The visual art leads an change of paradigm by images giving up the visual resemblance or the function of representation and endowing them with the new sense. This essay has a purpose to study an important discussion about this change centered on Baudrillard and Lacan. A sociologist Baudrillard promotes the concept of 'simulation' through detecting the reality and the social and historical state of the image. Studying on the course of this change, he calls the step that the image escapes from the stage to reflect the reality and become the pure imitation by itself simulation. The image in the stage of simulation is called 'hyperreality' because it doesn't have any an indicator or a substitute and happens by models without the original or the reality. So he asserts that art is not to contain some absoluteness or transcendency as the past, but to be as the spectacle with characteristics of meaningless, emptiness, contingency. Lacan dismantles the concept of the absolute Cogito to have become the center of the western ideology, and creates the concept of 'Other'. He concludes also the reality exists but can't be captured, and it's impossible for the thinking subject can reach it. The concept of new image which can be thought as the Symbolic in Lacan is 'Signifier without Signified' since it isn't possible to be the transcendent Signifier fixing the meaning finally in it. His 'Gaze' theory is which to be emitted in other's area determines the subject. Equally Baudrillard and Lacan sets up the new state of the image through the end of representation system As for Baudrillard, art intends to the worthlessness and is nothing but imagination. But in Lacan a picture represents the subject being in process by the dialectic of desire.

• 만화애니메이션 연구
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• 통권16호
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• pp.113-124
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• 2009

이 논문은 2D애니메이션의 표현적 색채를 집중적으로 고찰해봄으로써, 3차원적 공간을 탈피한 애니메이션의 색채가 실사 영화와의 근원적 차이를 보여 주고 있음을 밝히고자 하였다. 재현의 대상이 분명한 매체인 실사 영화와는 달리 2D애니메이션의 이미지는 기계적 재현의 과정을 거치지 않은 인간에 의한 창작물이며, 그것이 드러나는 첨예한 현상이 애니메이션의 표현적 색채라 할 수 있다. 따라서 2D애니메이션에서 표현적 색채는 애니메이션 이미지의 자율적인 의미가 드러나는 중요한 지점이 된다.

• IEIE Transactions on Smart Processing and Computing
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• 제6권4호
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• pp.262-268
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• 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.

• 전자공학회논문지
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• 제52권5호
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• pp.136-146
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• 2015

차량 인식을 기반으로 하는 능동 제어는 지능형 자동차의 구현에 필요한 핵심 기술이며. 차폐 영역(occlusion)이 빈번하게 발생하는 도심에서 차량을 인식하기 위하여 차량의 부분적인 모습만으로도 차량을 인식할 수 있는 부분 기반 차량 표현이 필요하다. 본 논문에서는 지역적인 특징을 기저벡터로 사용하는 비음수 텐서 분해(non-negative tensor factorization, NTF)를 이용하여 차량을 표현하고, NTF 분해 계수를 특징으로 차량 인식률을 검증하였다. 실험 결과, 제안하는 방법이 기존의 비음수 행렬 분해를 사용한 경우에 비하여 보다 직관적인 부분 표현이 가능하며, 도심 영상에서도 보다 강건하게 차량을 인식함을 보여주었다.

• 한국지능시스템학회논문지
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• 제11권6호
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• pp.454-458
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• 2001

이 논문에서는 디지털 영상의 퍼지 시스템 표현으로부터 유도된 Edge 검출 알고리듬에 대하여 기술한다. 이 알고리듬은 Gradient을 기반으로 한 것으로 Convolution Kernel이 기존의 Roberts, Prewitt 또는 Sobel등이 제안한 Gradient Kernel과 다른 새로운 것이다. 사용한 퍼지시스템은 디지털 영상을 근사적으로 표현한 Bicubic Spline 함수를 퍼지시스템 화한것으로서 2차 도함수가 연속이기 때문에 Gradient나 Laplacian 연산이 가능하다. Grid 점들에서 이 함수의 Gradient는 두 개의 축 방향으로 각각 한개의 3$\times$3행렬과 영상과의 Covolution에 의하여 산출됨을 보였으며 이를 이용하여 검출된 Edge들은 기존의 다른 방법을 사용하여 검출된 Edge 영상보다 훨씬 선명함을 확인하였다. 이 알고리듬 적용사례 2개에 대한 기술에 포함되어 있다.

• Current Optics and Photonics
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• 제4권3호
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• pp.210-220
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• 2020

Aiming at the problem that the Local Sparse Difference Index algorithm has low accuracy and low efficiency when detecting target anomalies in a hyperspectral image, this paper proposes a Weighted Collaborative Representation and Sparse Difference-Based Hyperspectral Anomaly Detection algorithm, to improve detection accuracy for a hyperspectral image. First, the band subspace is divided according to the band correlation coefficient, which avoids the situation in which there are multiple solutions of the sparse coefficient vector caused by too many bands. Then, the appropriate double-window model is selected, and the background dictionary constructed and weighted according to Euclidean distance, which reduces the influence of mixing anomalous components of the background on the solution of the sparse coefficient vector. Finally, the sparse coefficient vector is solved by the collaborative representation method, and the sparse difference index is calculated to complete the anomaly detection. To prove the effectiveness, the proposed algorithm is compared with the RX, LRX, and LSD algorithms in simulating and analyzing two AVIRIS hyperspectral images. The results show that the proposed algorithm has higher accuracy and a lower false-alarm rate, and yields better results.