• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.11-14
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• 2002

게임에서 충돌탐지는 게임의 성능향상을 위해 중요하다. 본 논문에서는 효율적인 충돌탐지를 위해 BSP 트리를 사용한다. 공격에 사용되는 스프라이트와 공격의 대상이 되는 스프라이트를 트리로 구성하여 빠른 시간내에 충돌탐지를 행한다. 또한 스프라이트의 모양에 따라 경계 볼륨(bounding volume)을 구와 박스(box)를 선택적으로 사용하여 충돌탐지에서 발생하는 문제점을 해결한다.

• Smart Media Journal
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• v.1 no.4
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.660-667
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• 2000

In this paper, a word segmentation method for handwritten Korean text line images is proposed. The method uses gap information to segment words in line images, where the gap is defined as a white run obtained after vertical projection of line images. Each gap is assigned to one of inter-word gap and inter-character gap based on gap distance. We take up three distance measures which have been proposed for the word segmentation of handwritten English text line images. Then we test three clustering techniques to detect the best combination of gap metrics and classification techniques for Korean text line images. The experiment has been done with 305 text line images extracted manually from live mail pieces. The experimental result demonstrates the superiority of BB(Bounding Box) distance measure and sequential clustering approach, in which the cumulative word segmentation accuracy up to the third hypothesis is 88.52%. Given a line image, the processing time is about 0.05 second.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.210-216
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• 2009

Several empty-space leaping methods have been proposed for CPU-based volume ray casting. When sample points are located in semi-transparent cells, however, previous leaping methods perform unnecessary resamplings even if the scalar values on those points are confined within transparent range. A semi-transparent cells leaping method for volume ray casting using the Marching Cubes algorithm is proposed to solve this problem in our previous work. When a ray reaches a semi-transparent cell, our method performs in-out test between current sample point and the bounding box enclosing the triangles generated by the Marching Cubes. If the sample point lies on outside of the bounding box, we estimate the point is regarded as transparent. In this case, the ray advances to the next sample point without performing a resampling operation. We can frequently refer the tables for neighboring voxels, however, when we exploit conventional data structures of the Marching Cubes. We propose modified Marching Cubes tables for solving this problem.

• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.396-405
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• 2001

Usually it is difficult to extract facial regions in a complex image by using only a predetermined skin color. Expecially, it is more difficult to separate them from background regions that contains the skin color. This paper proposes a face detection method by using gradual range expansion of an initial skin color. By analyzing the skin color distribution several images that are collected in the Web, the range of dense distribution is selected as the range of the initial skin color. In each expanding step, expanded regions in the image are tested whether they can be actual facial regions by using the information of the shape of general face and the location of face organs. The shape of general face is modeled as an ellipse and the aspect ratio of its bounding box is used to define the shape constraint for faces. Only the eyes and lips are used as the face organs, which can be easily detected by extracting horizontal edges in the expanded regions. through several experiments, it is confirmed that the proposed method can detect exactly not only faces having partly distorted regions by highlight but also faces neighboring similar color regions.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.77-83
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• 2019

In this paper, we propose an object tracking algorithm based on color histogram and convolutional neural network model. In order to increase the tracking accuracy, we synthesize generic object tracking using regression network algorithm which is one of the convolutional neural network model-based tracking algorithms and a mean-shift tracking algorithm which is a color histogram-based algorithm. Both algorithms are classified through support vector machine and designed to select an algorithm with higher tracking accuracy. The mean-shift tracking algorithm tends to move the bounding box to a large range when the object tracking fails, thus we improve the accuracy by limiting the movement distance of the bounding box. Also, we improve the performance by initializing the tracking start positions of the two algorithms based on the average brightness and the histogram similarity. As a result, the overall accuracy of the proposed algorithm is 1.6% better than the existing generic object tracking using regression network algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.83-95
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• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.120-122
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• 2021

Currently, as demand for cars at home and abroad increases, the number of vehicles is decreasing and the number of vehicles is increasing. This is the main cause of the traffic jam. To solve this problem, it operates a high-ocompancy vehicle (HOV) lane, a multi-passenger vehicle, but many people ignore the conditions of use and use it illegally. Since the police visually judge and crack down on such illegal activities, the accuracy of the crackdown is low and inefficient. In this paper, we propose a system design that enables more efficient detection using imaging techniques using computer vision to solve such problems. By improving the existing vehicle detection method that was studied, the trigger was set in the image so that the detection object can be selected and the image analysis can be conducted intensively on the target. Using the YOLO model, a deep learning object recognition model, we propose a method to utilize the shift amount of the center point rather than judging by the bounding box in the image to obtain real-time object detection and accurate signals.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.523-530
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• 2024

Online, such as web pages and digital documents, have the ability to search for specific words or specific phrases that users want to search in real time. Printed materials such as printed books and reference books often have difficulty finding specific words or specific phrases in real time. This paper describes the development of a deep learning model for detecting text and a real-time character detection system using OCR for recognizing text. This study proposes a method of detecting text using the EAST model, a method of recognizing the detected text using EasyOCR, and a method of expressing the recognized text as a bounding box by comparing a specific word or specific phrase that the user wants to search for. Through this system, users expect to find specific words or phrases they want to search in real time in print, such as books and reference books, and find necessary information easily and quickly.

• Journal of Korea Game Society
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• v.1 no.1
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• pp.55-60
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• 2001

With rapid development of graphic hardware, researches on Virtual Reality and 3D Games have received more attention than before. For more realistic 3D graphic scene, objects were to be presented with lots of polygons and the number of objects shown in a scene was remarkably increased. Therefore, for effective visualization of large polygon models like this, view-frustum culling method, that visualizes only objects shown in the screen, has been widely used. In general, the bounding boxes that include objects are generated firstly, and the boxes are intersected with view-frustum to check whether object is in the visible area or not. Recently, an algorithm that can check in-out test of objects using OpenGL's selection mode, which is originally used to select the objects in the screen, is suggested. This algorithm is fast because it can use hardware acceleration. In this study, by implementing and applying this algorithm to large polygon models, we showed the efficiency of OpenGL assisted View-Frustum Culling algorithm. If this algorithm is applied to 3D games that have to process more complicated characters and landscapes, performance improvement can be expected.