• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.15-18
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• 2008

This paper proposes a method to reconstruct the 3-D face using structured light image. First of all, we suppose that each sight vector of a projector and camera are parallel. We project the structured light in the shape of lattice on the background to acquire the reference-structured light image. This image is used to calibrate the projector and camera. Since then, we acquire the face-structured light image which is projected the same structured light on the face. These two structured light images are used to reconstruct the 3-D face through the variation which is measured from the positional difference of feature vectors. In our experiment result, we could reconstruct the 3-D face image as recognize through these simple devices.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.518-528
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• 2001

In this paper, we firstly define a new combined segmentation measure and propose a segmentation algorithm using this measure. The combined segmentation measure is a weighted sum of intensity, motion, and a change segmentation measure that is extracted from the resulting image of the proposed change detector. The change segmentation measure is defined as an absolute change value difference between an pixel and its neighboring region from the eroded image, which results from morphological erosion filtering to eliminate many inaccurate components included in the resulting image of a conventional change detector. The change segmentation measure can be used as an efficient segmentation measure for the accurate segmentation of neighboring moving objects and static background regions. Therefore, the proposed combined segmentation measure can determine exact boundaries in the segmentation process of region-based coding even though the estimated motion vectors around the boundaries of moving objects and static background regions are inaccurate and the intensities around the boundaries are similar.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1293-1299
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• 2012

In this paper, a real-time vehicle detection and tracking algorithms is proposed. The vehicle detection could be processed using GMM (Gaussian Mixture Model) algorithm and mathematical morphological processing with HD CCTV camera images. The vehicle tracking based on separated vehicle object was performed using Euclidean distance between detected object. In more detail, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the next stage, candidated objects were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations dependent on distance and vehicle type in tunnel. The vehicle tracking performed using Euclidean distance between the objects in the video frames. Through computer simulation using recoded real video signal in tunnel, it is shown that the proposed system works well.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.365-369
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• 2012

We propose a vision-based method that estimates train position and movement for railway monitoring in which we use a fuzzy classifier to determine train states. The proposed method employs frame difference and background subtraction for estimating train motion and presence, respectively. These features are used as the linguistic variables of the fuzzy classifier. Experimental results show that the proposed method can correctly estimate train position and movement. Therefore the method can be used for railway monitoring systems which estimate crowd density or protect safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.85-95
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• 2003

This paper proposes a multiple moving objects tracking system which is adaptable itself to circumstances. Snake model is sensitive to the start position value because it does not accurately express contours of objects in complex image. It can be improved as the proposed system gets background images by using difference images, segments objects using neighborhood pixels and assesses the position feature values acquired on the start position value to deformable Snake model. And also the system can simplify complex background images and reduce search regions by the constituent points of a Snake laid in Positions of object. It is showed that the proposed system can be appBied to multiple moving vehicle racking systems by the experimental results of 30fps AVI file.

• Korean Institute of Interior Design Journal
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• v.26 no.5
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• pp.75-82
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• 2017

The aim of this study is to find phenomenological characteristics in the background and contents of Kenneth Frampton's architectural theories and their contribution to architectural phenomenology. His theories reflect on the interpretations of Modern architecture synchronically and diachronically. This difference makes Frampton have more concrete direction for architectural phenomenology. Hanna Arendt, who contribute to form Frampton's architectural theory, introduced various concepts of Heidegger's phenomenology to Frampton. And criticism of image centered late capitalism also act as a background for Frampton to relate to phenomenology. Frampton emphasized the importance of 'critical regionalism' and 'tectonic' as a poetics of construction as the resistance of globalization. All of these have relations to 'place' and 'perception' that are main themes of phenomenology. Frampton explains his theory with phenomenological terms and above all things, he assimilates concerns of architectural phenomenology with critical thinking. In these aspects, his theories can be recognized as playing an important role to the development of architectural phenomenology.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.67-72
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• 2005

Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6919-6922
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• 2014

Background: The cytological analysis of serous effusions is a common investigation and yields important diagnostic information. However, the distinction of reactive mesothelial cells from malignant cells can sometimes be difficult for the cytopathologist. Hence cost-effective ancillary methods are essential to enhance the accuracy of cytological diagnosis. The aim of this study was to examine the utility of nuclear morphometry in differentiating reactive mesothelial cells from malignant cells in effusion smears. Materials and Methods: Sixty effusion smears consisting of 30 effusions cytologically classified as malignant (adenocarcinomas) and 30 benign effusions showing reactive mesothelial cells were included in the study. ImageJ was used to measure the nuclear area, perimeter, maximal feret diameter, minimal feret diameter and the circularity. A total of ten representative cells were studied in each case. Results: Significant differences were found between benign and malignant effusions for the nuclear area, perimeter, maximal feret diameter and minimal feret diameter. No significant difference was found for circularity, a shape descriptor. Receiver operating characteristic (ROC) curve analysis revealed that nuclear area, perimeter, maximal feret diameter, and minimal feret diameter are helpful in discriminating benign and malignant effusions. Conclusions: Computerised nuclear morphometry is a helpful ancillary technique to distinguish benign and malignant effusions. ImageJ is an excellent cost effective tool with potential diagnostic utility in effusion cytology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.32-41
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• 2008

The moving object tracking in vision based observation using video uses difference method between GMM(Gaussian Mixture Model) based background and present image. In the case of racking object using binary image made by threshold, the object is merged not by object information but by Cast-Shadow. This paper proposed the method that eliminates Cast-Shadow using backpropagation Neural Network. The neural network is trained by abstracting feature value form training image of object range in 10-movies and Cast-Shadow range. The method eliminating Cast-Shadow is based on the method distinguishing shadow from binary image, its Performance is better(16.2%, 38.2%, 28.1%, 22.3%, 44.4%) than existing Cast-Shadow elimination algorithm(SNP, SP, DNM1, DNM2, CNCC).

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.92-101
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• 1993

This paper describes algorithms to extract license plates in vehicle images. Conventional methods perform preprocessing on the entire vehicle image to produce the edge image and binarize it. Hough transform is applied to the binary image to find horizontal and vertical lines, and the license plate area is extracted using the charateristics of license plates (the boundary information of license plates). Problems with this approach are that real-time processing is not feasible due to long processing time and that the license plate area is not extracted when lighting is irregular such as at night or when the plate boundary does not show up in the image. This research uses the gray level transition characteristics of license plates to verify the digit area by examining the digit width and the gray level difference between the background area the digit area, and then extracts the plate area by testing the distance between the verified digits. This research solves the probelm of failure in extracting the license plates due to degraded plate boundary as in the conventional methods and resolves the provlem of the time requirement by processing in real time such that practical application is possible.