• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.168-177
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• 2012

The search for relevant and actionable information is a key to achieving clinical and research goals in biomedicine. Biomedical information exists in different forms: as text and illustrations in journal articles and other documents, in images stored in databases, and as patients' cases in electronic health records. This paper presents ways to move beyond conventional text-based searching of these resources, by combining text and visual features in search queries and document representation. A combination of techniques and tools from the fields of natural language processing, information retrieval, and content-based image retrieval allows the development of building blocks for advanced information services. Such services enable searching by textual as well as visual queries, and retrieving documents enriched by relevant images, charts, and other illustrations from the journal literature, patient records and image databases.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.688-690
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• 2004

In this paper, we propose a new method of removing glasses from human frontal facial images. We first detect the regions occluded by the glasses, and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame, nor of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion, and we believe that this method can also be used to enhance the performance of face recognition systems.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.301-303
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• 2002

Subspace analysis is a popular method for multivariate data analysis and is closely related to factor analysis and principal component analysis (PCA). In the context of image processing (especially positron emission tomography), all data points are nonnegative and it is expected that both basis images and factors are nonnegative in order to obtain reasonable result. In this paper We present a sequential EM algorithm for rectified subspace analysis (subspace in nonnegativity constraint) and apply it to dynamic PET image analysis. Experimental results show that our proposed method is useful in dynamic PET image analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.409-414
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• 2007

Active Appearance Model is a well-known model that can represent a non-rigid object effectively. However, since it uses the fixed appearance model, the fitting results are often unsatisfactory when the imaging condition of the target image is different from that of training images. To alleviate this problem, incremental AAM was proposed which updates its appearance bases in an on-line manner. However, it cannot deal with the sudden changes of illumination. To overcome this, we propose a novel scheme to update the appearance bases. When a new person appears in the input image, we synthesize illuminated images of that person and update the appearance bases of AAM using it. Since we update the appearance bases using synthesized illuminated images in advance, the AAM can fit their model to a target image well when the illumination changes drastically. The experimental results show that our proposed algorithm improves the fitting performance over both the incremental AAM and the original AAM.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1332-1341
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• 1999

본 논문에서는 시간에 따라 위치 및 회전각도가 변하는 얼굴 영상을 분석하여 눈과 입을 추출하는 방법을 제안한다. 동영상에서의 얼굴 영역을 효과적으로 추적하기 위해 간편화된 칼만 필터를 제안하며, 예측된 얼굴 영역 내에서 얼굴의 회전 각도를 고려하여 수직 및 수평 프로파일을 적용함으로써 좀 더 정교하게 얼굴 구성요소를 추출한다. 제안한 방법의 효율성은 실험 결과를 통하여 보인다.Abstract We propose the method that extracts eyes and mouth of human by analysing facial image sequences which can change their positions and orientations along the time. We propose the simplified Kalman filter to track the area of human face efficiently in image sequences. We also devise the method of slant-compensation, so that the facial components could be extracted more accurately by using vertical and horizontal profiles of the compensated images. Finally, we show the effectiveness of the suggested method through experimental results.

• Agricultural and Biosystems Engineering
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• v.1 no.1
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• pp.22-29
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• 2000

The development of bio-response feedback control system known as the speaking plant approach has been a challenging task for plant production engineers and scientists. In order to achieve the aim of developing such a bio-response feedback control system, the primary concern should be to develop a practical non-invasive technique for monitoring plant growth. Those who are skilled in raising plants can sense whether their plants are under adequate water conditions or not, for example, by merely observing minor color and tone changes before the plants wilt. Consequently, using machine vision, it may be possible to recognize changes in indices that describe plant conditions based on the appearance of growing plants. The interpretation of image information of plants may be based on image features extracted from the original pictorial image. In this study, the performance of a finite element retina was optimized by a genetic algorithm. The optimized finite element retina was evaluated based on the performance of neural plant growth monitor that requires input data given by the finite element retina.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.188-190
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• 2011

Image interpolation is a technique that pervades many an application. Interpolation is almost never the goal in itself, yet it affects both the desired results and the ways to obtain them. In this paper, we proposed a technique that is capable to find out the error when the common two methods (bilinear and nearest neighbor interpolation) are applied on an image for rotation. The proposed technique also includes the comparison results of bilinear interpolation and nearest neighbor interpolation. Among them nearest neighbor interpolation gives us a better result regarding to the enhancement and due to least error. The error is found by using Mean Square Error (MSE).

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.712-714
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• 2005

Real-time 3D visualization of large datasets imposes a distributed architecture of the rendering system and dedicated hardware for image composition. Previous work on this domain has relied on prohibitively expensive cluster systems with hardware composition done by complicated schemes. In this paper we propose a low-cost hardware compositor fur a high performance visualization cluster. We show the system's design and the results obtained using Simulink [1] for our image composition scheme.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.482-484
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• 1998

Abstract : Multimedia data now one of the widely used information in all the fields as the fast developments of computer techniques have been made. Traditional database systems based on textual information have limitations when applied to multimedia information. This is because simple textual descriptions are ambiguous and inadequate for searching multimedia information for multimedia databases and digital libraries. Thus, especially for image data, which is one of the important multimedia information types, which can retrieve and browse image data on the basis of pictorial queries. Therefore, this paper presents an efficient method for describing texture information in image data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.411-420
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• 1999

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.