• 방송공학회논문지
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• 제24권1호
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• pp.186-189
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• 2019

영상 인페인팅(image inpainting)이란 입력 영상에 훼손되거나 빈 영영이 존재할 경우 이 영역을 자연스럽게 채워 영상을 복원해내는 영상처리 기법이다. 본 논문에서는 기존의 예제 기반(exemplar-based) 영상 인페인팅의 단점 중 하나인 텍스쳐 가비지(texture garbage)의 생성을 억제할 수 있는 새로운 영상 인페인팅 기법을 제시한다. 기존 기법과 달리 영상의 텍스쳐는 통계적으로 정적(stationary)이라는 가정 하에 정적인 소스 패치만을 후보 패치로 샘플링 한다. 이를 통해 주변 신호와 일치하지 않는 신호인 텍스쳐 가비지가 타겟 영역에 복사되는 것을 방지할 수 있다. 실험을 통해 제안 기법을 이용한 텍스쳐 합성이 기존 기법에 비해 더욱 자연스러운 영상 인페인팅 결과를 생성함을 확인한다.

• 반도체디스플레이기술학회지
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• 제7권4호
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• pp.13-18
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• 2008

This paper explores a content-based image retrieval framework with relevance feedback based on genetic algorithm (GA). This framework adopts GA to learn the user preferences using the similarity functions defined for all available descriptors. The objective of the GA-based learning methods is to learn the user preferences using the similarity functions and to find a descriptor combination function that best represents the user perception. Experiments were performed to validate the proposed frameworks. The experiments employed the natural image databases and color and texture descriptors to represent the content of database images. The proposed frameworks were compared with the other two relevance feedback methods regarding effectiveness in image retrieval tasks. Experiment results demonstrate the superiority of the proposed method.

• 한국컴퓨터정보학회논문지
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• 제17권4호
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• pp.51-58
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• 2012

최근 깊이영상을 기반으로 한 3D 기술이 3D 공간감지, 3D 영상획득, 3D 인터랙션, 3D 게임 등 다양한 분야에서 응용되고 있다. 깊이영상을 생성하기 위해서는 깊이 카메라를 이용하게 되는데, 이렇게 생성된 깊이영상의 화질을 개선하기 위한 다양한 시도들이 이루어지고 있다. 본 눈문에서는 이러한 깊이 카메라 기반의 3D 응용에 있어서 깊이 영상을 개선하기 위해 영역기반의 에지 검출기를 사용하는 방법을 제안한다. 제안된 방법은 제한된 환경에서의 깊이영상을 획득하는 과정에서 발생 할 수 있는 화질열화를 후처리 또는 전처리를 통해 개선함으로써 보다 향상된 깊이 영상을 제공한다. 다양한 실험결과를 통해서 개선된 깊이영상을 객관적 화질 평가를 위해 가상시점 참조 소프트웨어에 적용하여 비교함으로써 최대 0.42dB의 화질 향상을 확인하였다. 또한 영상의 실제 시청 환경과 가장 유사한 방법인 DSCQS(Double Stimulus Continuous Quality Scale)방법을 통해서 주관적 화질의 객관적 평가를 수행함으로써 개선된 깊이영상의 효용성을 다시 확인하였다.

• 한국문헌정보학회지
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• 제49권4호
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• pp.99-124
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• 2015

As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.417-426
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• 2023

To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

• International Journal of Internet, Broadcasting and Communication
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• 제7권1호
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• pp.36-41
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• 2015

This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.127-134
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• 2023

Existing studies on this topic have focused on the effect of online content quality on consumer attitudes and behavior, with very few illustrating the effect of influencer image on consumer attitudes and behavior. The purpose of this study intents to reveal how influencer image affect consumer behavior. We have developed an image transfer theory-based research model to reveal how influencers transfer their image to endorsed products to influence consumer behavior. The results show that influencer image positively affects satisfaction, which in turn affects the product's cognitive and affective images in the vlog. Moreover, it was found that a product's cognitive image and affective image influence consumer behavior intention. Furthermore, purchase experience exhibits significant differences in its path. Based on these results, the social media-related research theoretical implication will be offered, and managerial implications will be provided for foreign brand promotion strategies

• Journal of applied mathematics & informatics
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• 제9권2호
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• pp.793-806
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• 2002

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• 전자공학회논문지A
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• 제32A권10호
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• pp.51-63
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• 1995

In this paper, a new real-time optical image switching system based on the phase-typed BPEJTC is suggested. The phase filter mask which has the arbitrary position mapping function between input and output planes is constructed by using the modified JTPS of the BPEJTC. Then, the input image is convolved with this phase filter mask in the spatial frequency domain and through further Fourier transform the input image is switched to the new positions in the output correlation plane where the correlation peaks are occurred. And, based on the computer simulation results, the practical optical switched to the new positions in the output correlation plane where the correlation peaks are occurred. And, based on the computer simulation results, the practical optical switching system is opto-digitally constructed and through some experiments on image switching the possiblity of real-time implementation of the multiple optical image switching system by using the BPEJTC is suggeste.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.590-593
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• 2001

In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.