• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.201-206
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• 2003

In clinical practice, CT Angiography is a powerful technique for the visualziation of blood flow in arterial vessels throughout the body. However CT Angiography images of blood vessels anywhere in the body may be fuzzy if the patient moves during the exam. In this paper, we propose a novel technique for removing global motion artifacts in the 3D space. The proposed methods are based on the two key ideas as follows. First, the method involves the extraction of a set of feature points by using a 3D edge detection technique based on image gradient of the mask volume where enhanced vessels cannot be expected to appear, Second, the corresponding set of feature points in the contrast volume are determined by correlation-based registration. The proposed method has been successfully applied to pre- and post-contrast CTA brain dataset. Since the registration for motion correction estimates correlation between feature points extracted from skull area in mask and contrast volume, it offers an accelerated technique to accurately visualize blood vessels of the brain.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1468-1471
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• 2012

It is always a dream to recreate the experience of a particular place, the Panorama Virtual Reality has been interpreted as a kind of technology to create virtual environments and the ability to maneuver angle for and select the path of view in a dynamic scene. In this paper we examined an efficient algorithm for Image registration and stitching of captured imaged from a video stream. Two approaches are studied in this paper. First, dynamic programming is used to spot the ideal key points, match these points to merge adjacent images together, later image blending is use for smooth color transitions. In second approach, FAST and SURF detection are used to find distinct features in the images and a nearest neighbor algorithm is used to match corresponding features, estimate homography with matched key points using RANSAC. The paper also covers the automatically choosing (recognizing, comparing) images to stitching method.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.563-565
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• 2023

Acupuncture and acupressure apply needles or pressure to anatomical points for therapeutic benefit. The over 350 mapped acupuncture points in the human body can each treat various conditions, but anatomical variations make precisely locating these acupoints difficult. We propose a computer vision technique using the real-time hand and face tracking capabilities of the MediaPipe framework to identify acupoint locations. Our model detects anatomical facial and hand landmarks, and then maps these to corresponding acupoint regions. In summary, our proposed model facilitates precise acupoint localization for self-treatment and enhances practitioners' abilities to deliver targeted acupuncture and acupressure therapies.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1883-1890
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• 2013

Location detection technology (LDT) is one of the core techniques for location based service (LBS) in wireless communication for improving resource management and quality of services. The location of a mobile station (MS) is estimated using the time of arrival (TOA) technique based on three circles with centers corresponding to coordinates of three base stations (BSs) and radius corresponding to distances between MS and BSs. For accurately estimating the location of MS, three circles should meet at a point for the trilateration method, but they generally do not meet a point because the radius is increased depending on the number of time delay for estimating the distance between MS and BS and the carrier frequency. The increased three circles intersect at six points and the three intersection points among them should be generally placed close to coordinate of the location for the specific MS. In this paper, we propose the shortest distance algorithm for TOA trilateration method, to select three interior intersection points from entire six points. The proposed approach selects three intersection points with the shortest distances between coordinates of MS and intersection points and determines the averaged coordinate of the selected three points, as the location of the specific MS. We demonstrate the performance of the proposed algorithm using a typical computer simulation example.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.714-724
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• 2021

The point cloud content is immersive content recorded by acquiring points and colors corresponding to the real environment and objects having three-dimensional location information. When a point cloud content consisting of three-dimensional points having position and color information is enlarged and rendered, the gap between the points widens and an empty hole occurs. In this paper, we propose a method for improving the quality of point cloud contents through inverse transformation-based interpolation using depth information for holes by finding holes that occur due to the gap between points when expanding the point cloud. The points on the back are rendered between the holes created by the gap between the points, acting as a hindrance to applying the interpolation method. To solve this, remove the points corresponding to the back side of the point cloud. Next, a depth map at the point in time when an empty hole is generated is extracted. Finally, inverse transform is performed to extract pixels from the original data. As a result of rendering content by the proposed method, the rendering quality improved by 1.2 dB in terms of average PSNR compared to the conventional method of increasing the size to fill the blank area.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.657-664
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• 2001

It is possible to extract a 3D models from its multiple views using the self-calibration. Though it is possible to construct 3D models of objects from their multiple views, accuracy of 3D models depends on the fundamental matrix estimated between two views. In this paper, we show the fundamental matrix accuracy can be improved by taking a non-linear minimization technique. Furthermore, the corresponding points which are completely mismatches or have greater discrepancy errors in their locations, reduce the fundamental matrix accuracy. Thus, applying the Monte Carlo technique and the non-linear minimization Levenberg-Marquardt method to remove the outliers, we can estimate the fundamental matrix with the higher accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.59-64
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• 2001

In this paper it was proposed method that solve problems of method to segment region of zero disparity and algorithm that extract binocular disparity to estimate position of object by vergence movement of moving stereo cameras experimented to compare those. There was not change of density value almost in region that change of critcal value was not found almost in image, because a high critical value was set so that critical value may be kipt changelessly about all small regions in studied treatise so far. The corresponding points were extracted wrongly by the result. By because the characteristics of small region was evaluated by autocorrelation and the critical value was established that may be proportional to the autocorrelation value, it was confirmed that corresponding points are not extracted almost by mistake and binocular disparity could by extracted with high speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.2
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• pp.191-198
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• 2000

Digital photogrammetry in the implementation of GIS database plays an important role, with the demand for rapid data acquisition and quick updating. Here image matching represents a fundamental task of digital photogrammetry. No image matching algorithm provides a solution as complete as the one given by human vision which is reinforced by knowledge and intelligence capabilities. In this paper, if object space is smooth, we check the global similarity between a possible corresponding point pair and its neighbouring possible corresponding point pairs, detecting blunders; We define matching strength measurement. Besides this, we compute three-dimension coordinates of matching points by bundle adjustment method. Results of the test reveal that the proposed method can eliminate the incorrectly matched pairs efficiently and the accuracy of three-dimension coordinates of matching points come within an allowable error.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.164-174
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• 2015

In a real scenario, radiometric change has frequently occurred in the stereo image acquisition process using multiple cameras with geometric characteristics or moving a single camera because it has different camera parameters and illumination change. Conventional stereo matching algorithms have a difficulty in finding correct corresponding points because it is assumed that corresponding pixels have similar color values. In this paper, we present a new method based on the local descriptor reflecting intensity, gradient and texture information. Furthermore, an adaptive weight for local descriptor based on the entropy is applied to estimate correct corresponding points under radiometric variation. The proposed method is tested on Middlebury datasets with radiometric changes, and compared with state-of-the-art algorithms. Experimental result shows that the proposed scheme outperforms other comparison algorithms around 5% less matching error on average.