• Journal of Environmental Science International
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• v.25 no.8
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• pp.1165-1176
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• 2016

The accuracy of digital elevation models (DEMs) is crucial for properly estimating flood inundation area. DEM pixel size is especially important when generating flood inundation maps of small streams with a channel width of less than 50 m. In Korea, DEMs with large spatial resolutions of 30 m have been widely applied to generate flood inundation maps, even for small streams. Additionally, when making river master plans, field observations of stream cross-sections, as well as reference points in the middle of the river, have not previously been used to enhance the DEM. In this study, it was graphically demonstrated that high-resolution DEMs can increase the accuracy of flood inundation mapping, especially for small streams. Also, a methodology was proposed to modify the existing low-resolution DEMs by adding additional survey reference points, including river cross-sections, and interpolating them into a high spatial resolution DEM using the inverse distance weighting method. For verification purposes, the modified DEM was applied to Han stream on Jeju Island. The modified DEM showed much better accuracy when describing morphological features near the stream. Moreover, the flood inundation maps were formulated with the original 30 m pixel DEM and the modified 0.1 m pixel DEM using HEC-RAS modeling of the actual flood event of Typhoon Nari, and then compared with the flood history map of Nari. The results clearly indicated that the modified DEM generated a similar inundation area, but a very poor estimate of inundation area was derived from the original low-resolution DEM.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.47-54
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• 2001

The main purpose of this study is to propose the algorithm about the extraction of the facial feature. To achieve the above goal, first of all, this study produces binary image for input color image. It calculates area after pixel labeling by variant block-units. Secondly, by contour following, circumference have been calculated. So the proper degree of resemblance about area, circumference, the proper degree of a circle and shape have been calculated using the value of area and circumference. And Third, the algorithm about the methods of extracting parameters which are about the feature of eyes, nose, and mouse using the proper degree of resemblance, general structures and characteristics(symmetrical distance) in face have been accomplished. And then the feature parameters of the front face have been extracted. In this study, twelve facial feature parameters have been extracted by 297 test images taken from 100 people, and 92.93 % of the extracting rate has been shown.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.304-310
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• 2009

In this paper, target extraction method in FLIR(forward-looking infrared) images based on fuzzy thresholding which used bi-modality and adjacency to determine membership value is proposed. The bi-modality represents how a pixel is classified into a part of target using distribution of pixel values in a local region, and The adjacency is a measure to represent how each pixel is far from the target region. First, membership value is calculated using above two measures, and then fuzzy thresholding is performed to extract the target. To evaluate performance of proposed target extraction method, we compare other segmentation methods using various FLIR tank image. Experimental results show that the proposed algorithm is a good segmentation performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.16-23
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• 2011

Muzzle flash based on gunnery is the target that has huge energy. So, gunnery target in a long range over xx km is distinguishable in the IR(infrared) images, on the other hand, is not distinguishable in the CCD images. In this paper, we propose the classification method of gunnery targets in a infrared images and in a long range. The energy from gunnery have an effect on varous pixel values in infrared images as a property of infrared image sensor, distance, and atmosphere, etc. For this reason, it is difficult to classify gunnery targets using pixel values in infrared images. In proposed method, we take the profile of pixel values using high performance infrared sensor, and classify gunnery targets using modeling GMM and shape of profile. we experiment on the proposed method with infrared images in the ground and aviation. In experimental result, the proposed method provides about 93% classification rate.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.15-19
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• 2015

The depth information of an image is used in a variety of applications including 2D/3D conversion, multi-view extraction, modeling, depth keying, etc. There are various methods to acquire depth information, such as the method to use a stereo camera, the method to use the depth camera of flight time (TOF) method, the method to use 3D modeling software, the method to use 3D scanner and the method to use a structured light just like Microsoft's Kinect. In particular, the depth camera of TOF method measures the distance using infrared light, whereas TOF sensor depends on the sensitivity of optical light of an image sensor (CCD/CMOS). Thus, it is mandatory for the existing image sensors to get an infrared light image by bundling several pixels; these requirements generate a phenomenon to reduce the resolution of an image. This thesis proposed a measure to acquire a high-resolution image through gradual area movement while acquiring a low-resolution image through pixel bundling method. From this measure, one can obtain an effect of acquiring image information in which illumination intensity (lux) and resolution were improved without increasing the performance of an image sensor since the image resolution is not improved as resolving a low-illumination intensity (lux) in accordance with the gradual pixel bundling algorithm.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.965-972
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• 2020

Depth maps have distance information of objects. They play an important role in organizing 3D information. Color and depth images are often simultaneously obtained. However, depth images have lower resolution than color images due to limitation in hardware technology. Therefore, it is useful to upsample depth maps to have the same resolution as color images. In this paper, we propose a novel method to upsample depth map by shifting the pixel position instead of compensating pixel value. This approach moves the position of the pixel around the edge to the center of the edge, and this process is carried out in several steps to restore blurred depth map. The experimental results show that the proposed method improves both quantitative and visual quality compared to the existing methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.44-49
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• 2016

This paper proposed the method to improve performance of a pixel, which has low accuracy, by applying image segmentation methods based on color and multi-threshold of brightness. Stereo matching is the process to find the corresponding point on the right image with the point on the left image. For this process, distance(depth) information in stereo images is calculated. However, in the case of a region which has textureless, stereo matching has low accuracy and bad pixels occur on the disparity map. In the proposed method, the relationship between adjacent pixels is considered for compensating bad pixels. Generally, the object has similar color and brightness. Therefore, by considering the relationship between regions based on segmented regions by means of color and multi-threshold of brightness respectively, the region which is considered as parts of same object is re-segmented. According to relationship information of segmented sets of pixels, bad pixels in the disparity map are compensated efficiently. By applying the proposed method, the results show a decrease of nearly 28% in the number of bad pixels of the image applied the method which is established.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.10-21
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• 2000

The Cellular Noninear Networks structure for Distance Transform(DT) and the robust optical flow detection algorithm based on the DT are proposed. For some applications of optical flows such as target tracking and camera ego-motion computation, correct optical flows at a few feature points are more useful than unreliable one at every pixel point. The proposed algorithm is for detecting the optical flows on the trajectories only of the feature points. The translation lengths and the directions of feature movements are detected on the trajectories of feature points on which Distance Transform Field is developed. The robustness caused from the use of the Distance Transform and the easiness of hardware implementation with local analog circuits are the properties of the proposed structure. To verify the performance of the proposed structure and the algorithm, simulation has been done about various images under different noisy environment.

• Journal of IKEEE
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• v.18 no.4
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• pp.478-484
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• 2014

In this paper, we propose new algorithm for positioning of mouse cursor using fingertip direction on kinect depth camera. The proposed algorithm uses center of parm points from distance transform when fingertip point toward screen. Otherwise, algorithm use fingertip points. After image preprocessing, the center of parm points is calculated from distance transform results. If the direction of the finger towards the camera becomes close to the distance between the fingertip point and center of parm point, it is possible to improve the accuracy of positioning by using the center of parm point. After remove arm on image, the fingertip points is obtained by using a pixel on the long distance from the center of the image. To calculate accuracy of mouse positioning, we selected any 5 points. Also, we calculated error rate between reference points and mouse points by performed 500 times. The error rate results could be confirmed the accuracy of our algorithm indicated an average error rate of less than 11%.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1474-1486
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• 2010

In this paper, we propose an algorithm which represents the distance depiction technique of real painting that named "Aerial Perspective" in painterly rendering. It is a painting technique that depicts the attenuations of light in the atmosphere, and the scattering effect is changed by the distance, altitude and density of atmospheres. For the reflection of these natures, we use the depth information corresponding to an input image and user-defined parameters, so that user changes the effect level. We calculate the distance and altitude of every pixel with the depth information and parameters about shot information, and control the scattering effects by expression parameters. Additionally, we accentuate the occluding edges detected by the depth information to clarify the sense of distance between fore and back-ground. We apply our algorithm on various landscape scenes, and generate the distance-emphasized results compared to existing works.