• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.450-460
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• 2005

Today, multimedia information is used on the internet and various social areas by rapid development of computer and communication technology. Therefor, the usage is growing dramatically. Multimedia information analysis system is basically based on text. So, there are many difficult problems like expressing ambiguity of multimedia information, excessive burden of works in appending notes and a lack of objectivity. In this study, we suggest a method which uses color and shape information of multimedia image partitions efficiently analyze a large amount of multimedia information. Partitions use field growth and union method. To extract color information, we use distinctive information which matches with a representative color from converting process from RGB(Red Green Blue) to HSI(Hue Saturation Intensity). Also, we use IMI(Improved Moment Invariants) which target to only outline pixels of an object and execute computing as shape information.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.111-115
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• 2009

This paper is related to a skinny smudge tool based on the image segmentation for a master shape. The smudge tool is the popular graphic tool embedded in Adobe Photoshop. The smudge tool is used to smear paint on your canvas. The effect is much like finger painting. You can use the smudge tool by clicking on the smudge icon and clicking on the canvas and while holding the mouse button down, dragging in the direction you want to smudge. A disadvantage of previous smudge tool is to also smear pixels in the undesired region according to generating the target image as blending all pixels in a diameter of the master. In this paper to reduce the disadvantage, the skinny smudge tool based on the image segmentation for a master shape is proposed. The proposed skinny smudge tool has the advantage of applying the smudge effect to the desired regions regardless of the background as the master shape adhered closely to the contour shape is extracted by color image segmentation.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.115-122
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• 2013

Disease diagnostics based on medical imaging is getting popularity day by day. Presence of the atherosclerosis is one of the causes of narrowing of carotid arteries which may block partially or fully blood flow into the brain. Serious brain strokes may occur due to such types of blockages in blood flow. Early detection of the plaque and taking precautionary steps in this regard may prevent from such type of serious strokes. In this paper, we present an automatic image segmentation technique for carotid artery ultrasound images based on active contour approach. In our experimental study, we assume that ultrasound images are properly aligned before applying automatic image segmentation. We have successfully applied the automatic segmentation of carotid artery ultrasound images using snake based model. Qualitative comparison of the proposed approach has been made with the manual initialization of snakes for carotid artery image segmentation. Our proposed approach successfully segments the carotid artery images in an automated way to help radiologists to detect plaque easily. Obtained results show the effectiveness of the proposed approach.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.173-182
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• 1998

As a result of remarkable developments in multimedia technology, the image database system that can efficiently retrieve image data becomes a core technology of information-oriented society. In this paper, we proposed the 2-phase Image Retrieval System considering both color and shape information as the method of image features extraction for content-based image data retrieval. At the first level, to get color information, with improving and extending the indexing method using color distribution characteristic suggested by Striker et al., i.e. the indexing method considering local color distribution characteristics, the system roughly classifies images through the improved method. At the second level, the system finally retrieves the most similar image from the image queried by the user using the shape information about the image groups classified at the first level. To extract the shape information, we use the Improved Moment Invariants (IMI) that manipulates only the pixels on the edges of objects in order to overcome two main problems of the existing Moment Invariant methods large amount of processing and rotation sensitiveness which can frequently be seen in the Directive Histogram Intersection technique suggested by Jain et al. Experiments have been conducted on 300 automobile images. And we could obtain the more improved results through the comparative test with other methods.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.191-199
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• 2009

In this paper, the improved edge extract methods is proposed in order to extract edge. For the correct and fast detect, the binary image using the threshold value is applied for a experiment. For the experimental analysis, we compare the existing edge methods with the improved methods. Hereby, the exist methods are the sobel, robert, and prewitt. and the improved methods use the existing methods which is applied mask variations. The merits of the improved mothods have a result of a little erosion, a apparent edge. Specially, we use the grey image of medical image for the experimental analysis and then apply threshold value for a result image. After that, we acquire a apparent edge. For a quantitative analysis of the each methods, the each images was applied a histogram. As a result, we prove the merit of the improved methods using a analytical graph of the medical images.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.1-11
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• 2004

It is very important part of pre-processing for get better results by image processing that get emphasized image by processing of source image. Emphasized image is not only good looking image but clear and sharp image. Emphasized images are used very useful data at contour extraction and image recognition in image processing. It have different image recognition by how much represent a origin scene in row quality image. Present algorithms that get emphasized premier image do not get clear picture of degree that want in various kind of images and there is shortcoming that need much process times being proportional size of picture quality or accumulation degree of histogram. In this paper, we propose method to change distribution chart that pixels occupy in histogram as subsequentness in reflex of various kinds as well as that picture quality reflex method to emphasize so that is suitable in practical use purpose originally of premier. Proposed algorithm re-allot histogram distribution by reverse tracking histogram. Experimental images are same result and take less processing time than histogram equalization.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.776-783
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• 2009

This paper is related to a 2D virtual color hairstyler using skinny smudge tool. The smudge tool is the popular graphic tool embedded in Adobe Photoshop. The smudge tool is used to smear paint on your canvas. The effect is much like finger painting. You can use the smudge tool by clicking on the smudge icon and clicking on the canvas and while holding the mouse button down, dragging in the direction you want to smudge. A disadvantage of previous smudge tool is to also smear pixels in the undesired region according to generating the target image as blending all pixels in a diameter of the master. In this paper to reduce the disadvantage, the skinny smudge tool based on the image segmentation for a master shape is proposed. The proposed skinny smudge tool has the advantage of applying the smudge effect to the desired regions regardless of the background as the master shape adhered closely to the contour shape is extracted by color image segmentation.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.239-245
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• 2014

In this paper, a weighted value wrinkle detection method is suggested based on the analysis on the entire facial features such as face contour, face size, eyes and ears. Firstly, the main facial elements are detected with AAM method entirely from the input screen images. Such elements are mainly composed of shape-based and appearance methods. These are used for learning the facial model and for matching the face from new screen images based on the learned models. Secondly, the face and background are separated in the screen image. Four points with the biggest possibilities for wrinkling are selected from the face and high wrinkle weighted values are assigned to them. Finally, the wrinkles are detected by applying Canny edge algorithm for the interested points of weighted value. The suggested algorithm adopts various screen images for experiment. The experiments display the excellent results of face and wrinkle detection in the most of the screen images.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.897-902
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• 2007

인간과 컴퓨터간의 전통적인 인터페이스는 인간이 요구하는 다양한 인터페이스를 제공하지 못한다는 점에서 점차 사용하기 불편하게 되었고 이는 새로운 형태의 인터페이스에 대한 요구로 이어지게 되었다. 본 논문에서는 이러한 추세에 맞추어 카메라를 통해 인간의 손 제스처를 인식하는 새로운 인터페이스를 연구하였다. 손은 자유도가 높고 3차원의 view direction에 의해 형상이 매우 심하게 변한다. 따라서 윤곽선 기반방법과 같은 2차원으로 투영된 영상에서 contour나 edge의 정보로 손 제스처를 인식하는 데는 한계가 있다. 그러나 모델기반 방법은 3차원 정보를 이용하기 때문에 손 제스처를 인식하는데 좋으나 계산량이 많아 실시간으로 처리하기가 쉽지 않다. 이러한 문제점을 해결하기 위해 손 형상에 대한 대규모 데이터베이스를 구성하고 정규화된 공간에서 Feature 간의 연관성을 파악하여 훈련 데이터 모델을 구성하여 비교함으로써 실시간으로 손 포즈를 구별할 수 있다. 이러한 통계적 학습 기반의 알고리즘은 다양한 데이터와 좋은 feature의 검출이 최적의 성능을 구현하는 것과 연관된다. 따라서 배경으로부터 노이즈를 최대한 줄이기 위해 피부의 색상 정보를 이용하여 손 후보 영역을 검출하고 검출된 후보 영역으로부터 HLF(Haar-like Feature)를 이용하여 손 영역을 검출한다. 검출된 손 영역으로부터 패턴 분류 과정을 거쳐 손 포즈를 인식 하게 된다. 패턴 분류 과정은 HLF를 이용하여 손 포즈를 인식하게 되는데 미리 학습된 각 포즈에 대한 HLF를 이용하여 손 포즈를 인식하게 된다. HLF는 Violar가 얼굴 검출에 적용한 것으로 얼굴 검출에 좋은 결과를 보여 주었으며, 이는 적분 이미지로부터 추출한 HLF를 이용한 Adaboost 학습 알고리즘을 사용하였다. 본 논문에서는 피부색의 색상 정보를 이용 배경과 손 영상을 최대한 분리하여 배경의 대부분이 Adaboost-Haar Classifier의 첫 번째 스테이지에서 제거되는 방법을 이용하여 그 성능을 더 향상 시켜 손 형상 인식에 적용하였다.