• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.191-196
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• 2021

In this paper, we implemented an image sensor module possible of detecting color temperature in an indoor environment. The color temperature information in the video information acquired by the image sensor was matched with a color difference illuminometer to produce an LUT. An algorithm was developed so that color temperature information according to the received RGB values can be automatically calculated. As a result of measuring the color temperature with an image sensor indoors, an accurate result of less than 5.91% was obtained compared to the reference value. It was confirmed that the uniformity of 23.5% or more was excellent compared to the color temperature measurement result using a color sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.225-230
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• 2009

We propose a template matching method for component inspection of SMD assembly system. To discriminate wrong assembled components, the input image of component is matched with its standard image by template matching algorithm. For a fast inspection system, the calculation time of matching algorithm should be reduced. Since the standard images of all components located in a PCB are stored in computer, it is desirable to reduce the memory size of standard image. We apply the discrete wavelet transformation to reduce the image size as well as the calculation time. Only 7% memory of the BMP image is used to discriminate goodness or badness of components assembly. Comparative results are presented to verify the usefulness of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.7-12
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• 2011

In this paper, we propose the technique detecting interest object region effectively in the images from periscope of submarine based on self-generated template. First, we extract the sea-sky line, and divide it into sky and sea area from background region based on the sea-sky line. In each divided background region, the blocks which can be represented in each background region are set as a reference template. After dividing an image into several same size of blocks, we apply multi template matching to the divided search blocks and histogram template to divide the image into object region and background region. Proposed algorithm is adapted to various images in which objects exist in the background of sea and sky. We verified that proposed algorithm performed properly without given informmed prby prior learning.ropso, regardless of the slope of sea-sky line and the locmed p of object based on sea-sky line, we verified that the objects region was segmented effectively from the input image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.105-116
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• 1999

Owing to the rapid development of computer system and the introduction of image processing technique, recent photogrammetric studies have been concentrated on the automation of photogrammetric orientation work that have been carried out by skilled professionals in analog and/or analytical pbotogrammetric field. To automate the whole photogrammetric work, the automation of the orientation processes including interior, relative and absolute orientation should be preceded. This study aims to automate interior orientation and relative orientation process. For this purpose, we applied Hough transform to interior orientation process and object space matching technique to relative orientation process. As the result of this study, we can present a method to automate interior and relative orientation process that has been semi-automatically operated in most commercial digital photogrammetric workstations currently available.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.27-36
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• 2017

In almost industries, such as the logistics industry, marine fisheries, agriculture, industry, and services, small unmanned aerial vehicles are used for aerial photographing or closing flight in areas where human access is difficult or CCTV is not installed. Also, based on the information of small unmanned aerial photographing, application research is actively carried out to efficiently perform surveillance, control, or management. In order to carry out tasks in a mission-based manner in which the set tasks are assigned and the tasks are automatically performed, the small unmanned aerial vehicles must not only fly steadily but also be able to charge the energy periodically, In addition, the unmanned aircraft need to land automatically and precisely at certain points after the end of the mission. In order to accomplish this, an automatic precision landing method that leads landing by continuously detecting and recognizing a marker located at a landing point from a video shot of a small UAV is required. In this paper, it is shown that accurate and stable automatic landing is possible even if simple template matching technique is applied without using various recognition methods that require high specification in using low cost general purpose small unmanned aerial vehicle. Through simulation and actual experiments, the results show that the proposed method will be made good use of industrial fields.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.203-211
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• 2018

Dam discharge is carried out for the management of rivers and area around rivers due to rainy season or drought. Dam discharge should be based on an accurate understanding of the flow rate that can be accommodated in the river. Therefore, understanding the allowable storage capacity of river is an important factor in the management of the environment around the river. However, the methods using water level meters and images, which are currently used to determine the allowable flow rate of rivers, show limitations in terms of accuracy and efficiency. In order to solve these problems, this paper proposes a method to automatically calculate the allowable storage capacity of river based on the images taken by drone. In the first step, we create a 3D model of the river by using the drone images. This generation process consists of tiepoint extraction, image orientation, and image matching. In the second step, the allowable storage capacity is calculated by cross section analysis of the river using the generated river 3D model and the road and river layers in the target area. In this step, we determine the maximum water level of the river, extract the cross-sectional profile along the river, and use the 3D model to calculate the allowable storage capacity for the area. To prove our method, we used Bukhan river's data and as a result, the allowable storage volume was automatically extracted. It is expected that the proposed method will be useful for real - time management of rivers and surrounding areas and 3D models using drone.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.103-110
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• 2008

General lens, widely using in Photogrammetry, has narrow view, and have to adjust "Image-Registration Method" after obtain images and it need cost; economic, period of time. Recent days, there is various study that use wide-angle lens, usually for robotics field, put to practical use in photogrammetry instead of general lens. In this studies, distortion tendency of wide-angle lens and utilize the correction techniques suitable to wide-angle lens by the existing photographic survey methods. After carrying out the calibration of the wide-angle lens, we calculated the correction parameters, and then developed the method that convert the original image-point to new image-point correcting distortion. For authorization the developed algorithm, we had inspection about shape and position; there are approximately 2D RMSE of 3 pixel, cx = 2, and cy = 3 different.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.31-42
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• 2013

This paper proposes a photogrammetric rectification method based on Bayesian approach as a method that eliminates vertical parallax between stereo images to minimize visual fatigue of 3D contents. The image rectification consists of two phases; geometry estimation and epipolar transformation. For geometry estimation, coplanarity-based relative orientation algorithm was used in this paper. To ensure robustness for mismatch and localization error occurred by automation of tie point extraction, Bayesian approach was applied by introducing several prior constraints. As epipolar transformation perspective transformation was used based on condition of collinearity to minimize distortion of result images and modification for input images. Other algorithms were compared to evaluate performance. For geometry estimation, traditional relative orientation algorithm, 8-points algorithm and stereo calibration algorithm were employed. For epipolar transformation, Hartley algorithm and Bouguet algorithm were employed. The evaluation results showed that the proposed algorithm produced results with high accuracy, robustness about error sources and minimum image modification.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.522-534
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• 2002

In this paper, we propose a new object tracking system using stereo images to improve the performance of the automatic object tracking system. The existing object tracking system has optimum characteristics, but it requires a lot of computation. In the case of the image with a single eye, the system is difficult to estimate and track for the various transformation of the object. Because the stereo image by both eyes is difficult to estimate the translation and the rotation, this paper deals with the tracking method, which has the ability to track the image for translation for real time, with block matching algorithm in order to decrease the calculation. The experimental results demonstrate the usefulness of proposed system with the recognition rate of 88% in the rotation, 89% in the translation, 88% in various image, and with the mean rate of 88.3%.