• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.716-721
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• 1990

It is one of the essential task to determine the absolute location of mobile robot during its navigation. In this paper we propose an algorithm to calculate the distance and orientation of camera from landmark through the visual image of stripe typed landmark. Exact closed form solution of camera location is obtained with the correspondences from vertical line on mark plane to the intersection point of projected line with horizontal axis of image plane. It needs only one line image information, so that location determination can be processed in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1021-1028
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• 2009

In this paper, a location identification for a cleaning robot using a camera shooting forward a room ceiling which kas three point landmarks is introduced. These three points are made from a laser source which is placed on an auto charger. A fisheye lens covering almost 150 degrees is utilized and the image is transformed to a camera image grabber. The widly shot image has an inevitable distortion even if wide range is coverd. This distortion is flatten using an image warping scheme. Several vision processing techniques such as an intersection extraction erosion, and curve fitting are employed. Next, three point marks are identified and their correspondence is investigated. Through this image processing and image distortion adjustment, a robot location in a wide geometrical coverage is identified.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.67-71
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• 2016

This paper addresses a problem of defocus map recovery from single image. We describe a simple effective approach to estimate the spatial value of defocus blur at the edge location of the image. At first, we perform a re-blurring process using Gaussian function with input image, and calculate a gradient magnitude ratio with blurring amount between input image and re-blurred image. Then we get a full defocus map by propagating the blur amount at the edge location. Experimental result reveals that our method outperforms a reliable estimation of depth map, and shows that our algorithm is robust to noise, inaccurate edge location and interferences of neighboring edges within input image.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.10
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• pp.1541-1551
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• 2009

This study gives guidelines to pattern designing by supplying various images of the transformed shape of jeans with the location of the waistline and the pants silhouette. For this study, 9 kinds of sample cloths (100% cotton denim) were designed considering the laying measurement of the jeans with the location of the waistline and the pants silhouette. The images of each sample were evaluated after the measurement of the completed samples. Clothing and textiles specialists used a semantic differential scale as the evaluation method of the images. For the statistical analysis of the data, one way Anova and Duncan test were adopted using the SPSS 12.0 program. The results of this study are as follows: 1. The visual image by the location of waistline and the change of the pants silhouette is composed of 3 factors (attraction, fashion and comfort factors) of which the attraction factor is the most important factor. 2. The visual image is positive when the location of the waistline is in the low waist position. It is attractive, fashionable, and comfortable. The visual image is negative when the location of the waistline is in the position of the natural waist. 3. The visual image is attractive when the pants silhouette is a boot-cut and fashionable when the pants silhouette are skinny. The straight-cut is comfortable but the visual image is negative. 4. There is no correlation between visual image by the location of the waistline and the change of the pants silhouette.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

• The Research Journal of the Costume Culture
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• v.14 no.4
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• pp.609-624
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• 2006

The purpose of this study is to give the guideline to the pattern designing by supplying various images of the transformed shape of tailored collar with the location and angle of gorge line and laying measurement of the tailored collar while designing the tailored collar. The results of this study are as follows : Images of the sample at the case of 1cm of laying measurement looks 'urban', 'light', 'sharp', 'young', 'fashionable' and 'narrow' than that at the case of 7cm. When the laying measurement increases, the image of the sample looks more 'classical' and 'boorish'. The image of the sample 'light', 'sensuous' and 'young' at the case of sample of which laying measurements of the collar was 3cm. Second, at the case of sample whose laying measurements of the collar was 5cm, it was shown that the low location of gorge line made the image of the sample 'soft' and 'short'. On the other hand the image of the sample looked 'hard', 'keen' and 'long' by the high location of gorge line. Third, at the case of sample of which laying measurements of the collar was 7cm, low location of gorge line made the image of the sample look short. However, normal location of gorge line made the image of the sample looked 'fashionable'. The images of the samples of which laying measurements of the collar were 3cm, 5cm and 7cm, respectively, had changed with the angle of gorge line. First, the high angle of gorge line made the image of the sample 'rigid' and 'keen' at the case of sample of which laying measurements of the collar was 3cm. The high angle of gorge line made the image of the sample looked 'boorish' and 'singular'.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1683-1689
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• 2014

In this paper, we propose an image processing based time-frequency domain reflectometry(TFDR) in order to estimate the fault location of a cable. The Wigner-Ville distribution is used for analysis in both the time domain and the frequency domain when the conventional TFDR estimates the fault location in a cable. However, the Winger-Ville distribution is a bi-linear function, and hence the cross-term is occurred. The conventional TFDR cannot estimate the accurate fault location due to the cross-term in case the fault location is close to the position where the reference signal is applied to the cable. The proposed method can reduce the cross-term effectively using binarization and morphological image processing, and can estimate the fault location more accurately using the template matching based cross correlation compared to the conventional TFDR. To prove the performance of the proposed method, the actual experiments are carried out in some cases.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.25-33
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• 2007

In this paper, I propose a method which can enhance the visual quality of IRST images based on a loaded location in ship and an AOS. The IRST adjusts an AOS to detect targets with various altitudes because of its narrow vertical field of view and offers various functions to enhance images with its low contrast. In the proposed method, images are divided into two regions of sea and sky on the basis of the horizon after establishing relation between an AOS and a horizon location within an image. As a result, image enhancement of the proposed method is performed adaptively according to the divided region while that of conventional method is performed for entire image without the region division. Simulation results show that the proposed method represents higher visibility compared with conventional one.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.939-948
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• 2004

In this paper. we Propose a robust and fast image registration technique for motion correction in brain CT-CT angiography obtained from same patient to be taken at different time. First, the feature points of two images are respectively extracted by 3D edge detection technique, and they are converted to locally weighted 3D distance map in reference image. Second, we search the optimal location whore the cross-correlation of two edges is maximized while floating image is transformed rigidly to reference image. This optimal location is determined when the maximum value of cross-correlation does't change any more and iterates over constant number. Finally, two images are registered at optimal location by transforming floating image. In the experiment, we evaluate an accuracy and robustness using artificial image and give a visual inspection using clinical brain CT-CT angiography dataset. Our proposed method shows that two images can be registered at optimal location without converging at local maximum location robustly and rapidly by using locally weighted 3D distance map, even though we use a few number of feature points in those images.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.