• Science of Emotion and Sensibility
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• v.7 no.4
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• pp.57-65
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• 2004

In this paper, we present a hybrid approach which incorporates color, texture and shape in content-based image retrieval. Colors in each image are clustered into a small number of representative colors. The feature descriptor consists of the representative colors and their percentages in the image. A similarity measure similar to the cumulative color histogram distance measure is defined for this descriptor. The co-occurrence matrix as a statistical method is used for texture analysis. An optimal set of five statistical functions are extracted from the co-occurrence matrix of each image, in order to render the feature vector for eachimage maximally informative. The edge information captured within edge histograms is extracted after a pre-processing phase that performs color transformation, quantization, and filtering. The features where thus extracted and stored within feature vectors and were later compared with an intersection-based method. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1088-1095
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• 2009

In this paper, we describe the reorientation method of distorted road sign by using projection transformation for improving recognition rate of road sign. RSR (Road Sign Recognition) is one of the most important topics for implementing driver assistance in intelligent transportation systems using pattern recognition and vision technology. The RS (Road Sign) includes direction of road or place name, and intersection for obtaining the road information. We acquire input images from mounted camera on vehicle. However, the road signs are often appeared with rotation, skew, and distortion by perspective camera. In order to obtain the correct road sign overcoming these problems, projection transformation is used to transform from 4 points of image coordinate to 4 points of world coordinate. The 4 vertices points are obtained using the trajectory as the distance from the mass center to the boundary of the object. Then, the candidate areas of road sign are transformed from distorted image by using homography transformation matrix. Internal information of reoriented road signs is segmented with arrow and the corresponding indicated place name. Arrow area is the largest labeled one. Also, the number of group of place names equals to that of arrow heads. Characters of the road sign are segmented by using vertical and horizontal histograms, and each character is recognized by using SAD (Sum of Absolute Difference). From the experiments, the proposed method has shown the higher recognition results than the image without reorientation.

• Journal of Astronomy and Space Sciences
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• v.16 no.2
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• pp.217-266
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• 1999

The light curves of the representative 6 contact binary stars observed by OGLE Project of searching for dark matter in our Galaxy have been analyzed by the method of the Wilson and Devinney Differential Correction to find photometric solutions. The orbital inclinations of these Devinney Differential Correction to find photometric solutions. The orbital inclinations of these binaries are in the range of $52^{circ}-69^{\circ}$ which is lower than that of the solar neighborhood binaries. The Roche lobe filling factor of these binaries are distributed in large range of 0.12 - 0.90. Since absence of spectroscopic observations for these binaries we have found masses of the 6 binary systems based on the intersection between Kepler locus and locus derived from Vandenberg isochrones in the mass - luminosity plane. Then absolute dimensions and distances have been found by combining the masses and the photometric solutions. The distances of the 6 binary systems are distributed in the range of 1 kpc- 6 kpc. This distance range is the limiting range where the contact binaries which have period shorter than a day are visible. Most contact binaries discovered in the Baade window do not belong to the Galactic bulge.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.29-39
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• 2000

Position of stop line according to left turn trajectory at intersections was studied. The Purpose of this study is to suggest a design guideline of left turn trajectory at intersections which is related to the Position of cross road stop line. Distance from the curb line to the stop line at each lane was calculated and discussed for various combination of road widths. Three design vehicle type and three control radii were considered. Setbacks of stop line from the curb line are Proportional to the control radius which depends on type of design vehicle. 8m, lim and 19m setback for control radius of 12m, 15m and 23m were calculated respectively as their maximum value. This result will be helpful to Paint the road marking on the Pavement which is usually difficult to fit to the designated radius. Field study of the effect of left turn trajectory on flow rate and safety was conducted. It was approved that improperly designed left turn trajectory decreases left turn capacity and increases conflicts among left turn flows of the adjacent lane.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.70-80
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• 2012

In Vehicular Ad-hoc Network(VANET) which constructs networks without fixed infrastructure among vehicles, network topology is frequently changed due to high mobility. In case of urban model, communication disconnections caused by interruptions of communication propagation such as buildings and constructions could be often occurred. Therefore, in VANET environment a routing protocol to complement its characteristics is needed. This paper suggests an algorithm to improve the transmission performance at intersections by approaching of the distance-based broadcasting which utilizes the information of vehicle's position. By using relative velocity among vehicles, it makes the stability of route decision improved and reduces packet collisions through graded priorities in the intersection, and simultaneously improves the performance of data rate. It can be seen that the performance compared with previous algorithm is significantly improved when using the suggested algorithm in the urban traffic environment.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.29 no.3
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• pp.177-182
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• 1993

In order to estimate the mesh selectivity master curves and the optimum mesh size, experiments were made by the cover net method with the cod-ends of the five different the opening mesh sizes(51.2mm, 70.2mm, 77.6mm, 88.0mm and 111.3mm). After that 163 hauling were performed and there by investigated, on the training vessel Saebada in the Southern Korean Sea and East China Sea from June 1991 to August 1992. In this report, the mesh selectivity master curves were fitted by using logistic function(S=1/(1+exp super(-(aR+b))), R=(L-L sub(0))/(M-M sub(0)) and the optimum mesh sizes were estimated from each master curve. In this case, a and b are the selection parameters, M is the mesh size of each experimental cod-end. L is body length, L sub(0) and M sub(0) is the distance from the coordinate origine to intersection of linear regression between 25% and 50% selection length. The results obtained are summarized as follows; 1. Trachurus japonicus: Mesh selectivity master curve parameters: a and b were 2. 25, -4.73 respectively and optimum mesh size was estimated to be 79.3mm. 2. Trichiurus lepturus: Mesh selectivity master curve parameters: a and b were 0.81, -3.17 respectively and optimum mesh size was estimated to be 64.5mm. 3. Photololigo edulis: Mesh selectivity master curve parameters: a and b were 1.30m, -4.10 respectively and optimum mesh size was estimated to be 89.9mm. 4. Todarodes pacificus: Mesh selectivity master curve parameters: a and b were 1. 35, -3.45 respectively and optimum mesh size was estimated to be 89.4mm.

• Journal of KIISE
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• v.42 no.2
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• pp.227-234
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• 2015

This paper proposes a modified MI-SVM algorithm by considering data distribution. The previous MI-SVM algorithm seeks the margin by considering the "most positive" instance in a positive bag. Positive instances included in positive bags are located in a similar area in a feature space. In order to reflect this characteristic of positive instances, the proposed method selects the "most positive" instance by calculating the distance between each instance in the bag and a pivot point that is the intersection point of all positive instances. This paper suggests two ways to select the "most positive" pivot point in the training data. First, the algorithm seeks the "most positive" pivot point along the current predicted parameter, and then selects the nearest instance in the bag as a representative from the pivot point. Second, the algorithm finds the "most positive" pivot point by using a Diverse Density framework. Our experiments on 12 benchmark multi-instance data sets show that the proposed method results in higher performance than the previous MI-SVM algorithm.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.1
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• pp.58-65
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• 2019

The stability, reliability and efficiency of a smart ship are important issues as the interest in an autonomous ship has recently been high. An automatic collision avoidance system is an essential function of an autonomous ship. This system detects the possibility of collision and automatically takes avoidance actions in consideration of economy and safety. In order to construct an automatic collision avoidance system using reinforcement learning, in this work, the sequential decision problem of ship collision is mathematically formulated through a Markov Decision Process (MDP). A reinforcement learning environment is constructed based on the ship maneuvering equations, and then the three key components (state, action, and reward) of MDP are defined. The state uses parameters of the relationship between own-ship and target-ship, the action is the vertical distance away from the target course, and the reward is defined as a function considering safety and economics. In order to solve the sequential decision problem, the Deep Deterministic Policy Gradient (DDPG) algorithm which can express continuous action space and search an optimal action policy is utilized. The collision avoidance system is then tested assuming the $90^{\circ}$intersection encounter situation and yields a satisfactory result.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.91-100
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• 2023

The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

• Archives of Craniofacial Surgery
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• v.24 no.1
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• pp.18-23
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• 2023

Background: When performing reduction of zygomatic arch fractures, locating the inward portion of the fracture can be difficult. Therefore, this study investigated the discrepancy between the locations of the depression on the soft tissue and bone and sought to identify how to determine the inward portion of the fracture on the patient's face. Methods: We conducted a retrospective review of chart with isolated zygomatic arch fractures of type V in the Nam and Jung classification from March 2013 to February 2022. For consistent measurements, a reference point (RP), at the intersection between a vertical line passing through the end point of the root of the ear helix in the patient's side-view photograph and a transverse line passing through the longest horizontal axis of the external meatus opening, was established. We then measured the distance between the RP and the soft tissue depression in a portrait and the bone depression on a computed tomography (CT) scan. The discrepancy between these distances was quantified. Results: Among the patients with isolated zygomatic arch fractures, only those with a fully visible ear on a side-view photograph were included. Twenty-four patients met the inclusion criteria. There were four types of discrepancies in the location of the soft tissue depression compared to the bone depression: type I, forward and upward discrepancy (7.45 and 3.28 mm), type II, backward and upward (4.29 and 4.21 mm), type III, forward and downward (10.06 and 5.15 mm), and type IV, backward and downward (2.61 and 3.27 mm). Conclusion: This study showed that discrepancy between the locations of the depressions on the soft tissue and bone exists in various directions. Therefore, applying the transverse and vertical distances measured from a bone image of the CT scan onto the patient's face at the indicated RP will be helpful for predicting the reduction location.