• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.573-576
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• 1999

This paper presents a new shape segmentation algorithm. The procedure to achieve complete segmentation consists of two steps : the first step is mapping shape into two dimension by the using Distance Transform, the second step is partitioning the region by using the Watershed algorithm. As a application of the proposed algorithm, we perform the matching experiment for several objects by the use of segmented region. Simulation results demonstrate the efficiency of the proposed method, and the method has scale, rotation, and shift invariant properties.

• Journal of Sensor Science and Technology
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• v.18 no.1
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• pp.22-27
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• 2009

The GPS(global positioning system) made up of 28 artificial satellites going round around the earth at a height of 20,000.Km is a system to determine the receiver's location by measuring the distance between the satellite and receivers using an electronic wave. Recently it's been widely used in various applications, such as a navigator, a surveying system, etc. In this paper, we propose a new algorithm to transform coordinates from GPS signals corresponding to various sizes of maps, and the application using this algorithm is also introduced. The algorithm is programmed by MFC on the WinCE 5.0 operating system, and the GPS receiver with a 20 channel high sensitivity and GPS microcontroller chip manufactured by SiRF Technology was used.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.564-573
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• 2009

In this paper, we consider a wireless multiple path network in which a transmitting node would like to send a message to the receiving node with a certain probability of success. These two nodes are separated by N erasure paths, and we devise two algorithms to determine minimum redundancy and optimal symbol allocation for this setup. We discuss the case with N = 3 and then extend the case to an arbitrary number of paths. One of the algorithms minimum redundancy algorithm in exponential time is shown to be optimal in several cases, but has exponential running time. The other algorithm, minimum redundancy algorithm in polynomial time, is sub-optimal but has polynomial worstcase running time. These algorithms are based off the theory of maximum-distance separable codes. We apply the MRAET algorithm on maximum-distance separable, Luby transform, and Raptor codes and compare their performance.

• Journal of Biomedical Engineering Research
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• v.27 no.4
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• pp.189-196
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• 2006

Micro computed tomography (micro-CT) has been used for in vivo animal study owing to its noninvasive and high spatial resolution capability. However, the sizes of existing detectors for micro-CT systems are too small to obtain whole-body images of a small animal object with $\sim$10 micron resolution and a part of its bones or other organs should be extracted. So, we have introduced the zoom-in micro-tomography technique which can obtain high-resolution images of a local region of an live animal object without extracting samples. In order to verify our zoom-in technique, we performed in vivo animal bone study. We prepared some SD (Sprague-Dawley) rats for making osteoporosis models. They were divided into control and ovariectomized groups. Again, the ovariectomized group is divided into two groups fed with normal food and with calcium-free food. And we took 3D tomographic images of their femurs with 20 micron resolution using our zoom-in tomography technique and observed the bone changes for 12 weeks. We selected ROI (region of interest) of a femur image and applied 2D FDT (fuzzy distance transform) to measure the trabecular bone thickness. The measured results showed obvious bone changes and big differences between control and ovariectomized groups. However, we found that the reliability of the measurement depended on the selection of ROI in a bone image for thickness calculation. So, we extended the method to 3D FDT technique. We selected 3D VOI (volume of interest) in the obtained 3D tomographic images and applied 3D FDT algorithm. The results showed that the 3D technique could give more accurate and reliable measurement.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.303-312
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.3
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• pp.48-57
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• 2005

This paper presents a novel algorithm in order to extract lane-related information based on machine vision techniques. The algorithm makes up for the weak points of the former method, the Edge Distribution Function(EDF)-based approach, by introducing a Lane Boundary Pixel Extractor (LBPE) and the well-known Hough Transform(HT). The LBPE that serves as a filter to extract pixels expected to be on lane boundaries enhances the robustness of machine vision, and provides its results to the HT implementation and EDF construction. The HT forms the accumulator arrays and extracts the lane-related parameters composed of orientation and distance. Furthermore, as the histogram of edge magnitude with respect to edge orientation angle, the EDF has peaks at the orientations corresponding to lane slopes on the perspective image domain. Therefore, by fusing the results from the EDF and the HT the proposed algorithm improves the confidence of the extracted lane-related information. The system shows successful results under various degrees of illumination.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1697-1702
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• 2017

This paper proposes a forward vehicle movement estimation algorithm for the image-based forward collision warning. The road region in the acquired image is designated as a region of interest (ROI) and a distance look up table (LUT) is made in advance. The distance LUT shows horizontal and vertical real distances from a reference pixel as a test vehicle position to any pixel as a position of a vehicle on the ROI. The proposed algorithm detects vehicles in the ROI, assigns labels to them, and saves their distance information using the distance LUT. And then the proposed algorithm estimates the vehicle movements such as approach distance, side-approaching and front-approaching velocities using distance changes between frames. In forward vehicle movement estimation test using road driving videos, the proposed algorithm makes the valid estimation of average 98.7%, 95.9%, 94.3% in the vehicle movements, respectively.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.109-116
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• 2003

Space leaping is one of accelerated image-order volume rendering. This method accelerates rendering speed by finding and leaping the empty space. Although its rendering speed is very fast, it takes long pre-processing time to make the data structure to leap the space. In this paper we propose the look-ahead sampling algorithm to double the leaping distance comparing with previous approaches. This algorithm reduces the preprocessing time to make the distance map without significant changes of rendering time. Also, it accelerates the rendering time.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.113-116
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• 2002

In this paper, we propose the sound-mapping algorithm of the detected obstacle by ultrasonic sensors. We apply this algorithm to a Obstacle alarm for the visually impaired. In our system, we acquire obstacles information using ultrasonic sensors, and transform two-dimensional and distance information into sound-imaging information and vibrator with azimuth (direction) and distance. We implement this system with ultrasonic sensors to more effective expression of the obstacle information. The distance of an obstacle can be expressed by sound pressure level, and azimuth of the obstacles can be expressed by inter-aural time difference (ITD) and inter-aural level difference (ILD) that are two important cues in a binaural system. These are the principal cues for sound localization, to detect sound source. In this system, the obstacle is substituted with a sound source. The visually impaired receive sound information of obstacles by headphone.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.625-627
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• 2005

Existent distance measurement that use camera is method that use both Stereo Camera and Monocular Camera, There is shortcoming that method that use Stereo Camera is sensitive in effect of a lot of expenses and environment variables, and method that use Monocular Camera are big computational complexity and error. In this study, reduce expense and error using Monocular Camera and I suggest algorithm that measure distance, Extract features using scale Invariant features Transform(SIFT) for distance measurement, and this measures distance through features matching and geometrical analysis, Proposed method proves measuring distance with wall by geometrical analysis free wall through feature point abstraction and matching.