• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.215-224
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• 2011

There have been studying many researches to detect human body and to track one with increasing interest on human and computer interaction. In this paper, we propose the algorithm that automatically extracts joints, linked points of human body, using the ratio of human body under single camera and tracks object. The proposed method gets the difference images of the grayscale images and ones of the hue images between input image and background image. Then the proposed method composes the results, splits background and foreground, and extracts objects. Also we standardize the ratio of human body using face' length and the measurement of human body and automatically extract joints of the object using the ratio and the corner points of the silhouette of object. After then, we tract the joints' movement using block-matching algorithm. The proposed method is applied to test video to be acquired through a camera and the result shows that the proposed method automatically extracts joints and effectively tracks the detected joints.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.549-556
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• 2001

The general problems of recovering 3D for 2D imagery require the depth information for each picture element form focus. The manual creation of those 3D models is consuming time and cost expensive. The goal in this paper is to simplify the depth estimation algorithm that extracts the depth information of every region from monocular image sequence with camera translation to implement 3D video in realtime. The paper is based on the property that the motion of every point within image which taken from camera translation depends on the depth information. Full-search motion estimation based on block matching algorithm is exploited at first step and ten, motion vectors are compensated for the effect by camera rotation and zooming. We have introduced the algorithm that estimates motion of object by analysis of monocular motion picture and also calculates the averages of frame depth and relative depth of region to the average depth. Simulation results show that the depth of region belongs to a near object or a distant object is in accord with relative depth that human visual system recognizes.

• Smart Media Journal
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• v.5 no.1
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• pp.15-23
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• 2016

This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• The Journal of Bigdata
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• v.3 no.2
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• pp.51-57
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• 2018

The purpose of this study is to find a valid link between color and tourism experience. We analyzed color that extracted by Aerial photo by IRI Image Scale to find color image. As an indicator of the experience of tourism, a review of the Tripadvisor was selected and analyzed through text mining. Results using text mining results and IRI image scales were generally inconsistent. To identify problems with aerial photo, the results of the analysis using the representative photographs provided by the Tripadvisor in the same way were the same as before. This indicate that details are key of tourism than the image of the overall background. This study presents new research directions by combining color analysis studies with text mining.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.6
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• pp.677-683
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• 2008

The antioxidant activities of Wisteria floribunda flowers (WFF) were evaluated. The samples were prepared by extracting separately two different colored flowers (purple and white) with four different solvents (methanol, ethanol, acetone, and water). The antioxidant properties were evaluated by determining total phenolic contents (TPC), radical scavenging activity (RSA), and reducing power (RP). Water extract from purple WFF and ethanol extract of white WFF showed the highest total phenol contents (491 and 787 ${\mu}M$ gallic acid equivalents), respectively. Water extracts of purple and white WFF also showed higher RSA. In the case of RP, ethanol extract of purple WFF, methanol and water extracts of white WFF showed relatively higher values. The 200 ${\mu}M$ $H_2O_2$ induced oxidative DNA damage in human leukocytes was significantly inhibited with WFF extracts excluding ethanol and acetone extracts of purple flowers. These results suggest that W. floribunda flowers have significant antioxidative activity and protective effect against oxidative DNA damage.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.343-350
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• 2016

In this paper, We proposed a realtime smoke detection using hidden markov model and DWT. The smoke type is not clear. The color of the smoke, form, spread direction, etc., are characterized by varying the environment. Therefore, smoke detection using specific information has a high error rate detection. Dynamic Object Detection was used a robust foreground extraction method to environmental changes. Smoke recognition is used to integrate the color, shape, DWT energy information of the detected object. The proposed method is a real-time processing by having the average processing speed of 30fps. The average detection time is about 7 seconds, it is possible to detect early rapid.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.171-176
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• 2009

본 논문은 사용할 수 있는 헤어스타일의 수가 제한되는 문제를 해결하기 위한 것으로, 상호대화식 매팅을 이용한 2D 가상 컬러 헤어스타일러에 관한 것이다. 사전에 준비된 그래픽 헤어스타일 외에도 원하는 헤어스타일을 보유한 2D 실사 영상으로부터 상호대화식 매팅 기술을 사용하여 헤어스타일을 분리 추출한 후, 영상 간 픽 앤 드롭(pick-and-drop) 방식으로 옮겨와 두상에 부착한 다음, 필요시 헤어스타일의 컬러도 자유롭게 변경할 수 있는 기능을 제공함으로써 저비용으로 활용 가능한 헤어스타일의 수를 증대시킬 수 있다. 이때 헤어스타일의 분리 추출은 사용자가 전경 객체의 개략적 윤곽을 그려줌에 따라 점증적으로 알파 매트를 계산하는 상호대화식 매팅 기술을 사용한다. 그리고 헤어스타일의 컬러 변경은 명도 차분 맵(intensity difference map)에 기반한 모발 컬러 매핑 기술을 사용한다. 제안된 방법은 직관적이고 편리한 상호대화식 사용자 인터페이스를 제공하기 때문에 작업자의 피로도를 경감시킴과 동시에 작업 시간을 단축할 수 있고 비숙련자도 간단한 사용자 입력을 통해 자연스러운 가상 헤어스타일을 생성할 수 있는 장점이다.

• Journal of Advanced Navigation Technology
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• v.12 no.2
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• pp.164-169
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• 2008

This paper is using motion tracking by image segmentation to monitor intruders and to confirm based on mobile the relevant information. First, detect frame in animation that film fixed area, and make use of image subtraction between two frame that adjoin, segment fixed backing and target who move. Segmental foreground object to the edge detecting the location specified by the edge of the median estimate extracted by analyzing the motion of the intruders to monitor. When a motion is detected, the detected image is transmitted by using the W AP pull basis image transmission method on the mobile client data terminal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.282-287
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• 2002

This paper action tracing by techniques to do image sequence component to watch invader based on Mobile internet use. First, detect frame in animation that film fixed area, and make use of image subtraction between two frame that adjoin, segment fixed backing and target who move. Segmentalized foreground object detected and did so that can presume middle value of gouge that is abstracted to position that is specified and watch invader by analyzing action gouge. Those watch information is stored, and made Mobile client send out SMS Message about situation of watch place to server being stored to sensed serial numbers, date, Image file with recording of time.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.505-514
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• 2002

In this Paper, we propose a method of content-based image classification using neural network. The images for classification ate object images that can be divided into foreground and background. To deal with the object images efficiently, object region is extracted with a region segmentation technique in the preprocessing step. Features for the classification are texture and shape features extracted from wavelet transformed image. The neural network classifier is constructed with the extracted features and the back-propagation learning algorithm. Among the various texture features, the diagonal moment was more effective. A test with 300 training data and 300 test data composed of 10 images from each of 30 classes shows correct classification rates of 72.3% and 67%, respectively.