• Title/Summary/Keyword: 좌표분할

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Application of Deep Learning-based Object Detection and Distance Estimation Algorithms for Driving to Urban Area (도심로 주행을 위한 딥러닝 기반 객체 검출 및 거리 추정 알고리즘 적용)

  • Seo, Juyeong;Park, Manbok
    • 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.

A Study on the Improvement of the Facial Image Recognition by Extraction of Tilted Angle (기울기 검출에 의한 얼굴영상의 인식의 개선에 관한 연구)

  • 이지범;이호준;고형화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.7
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    • pp.935-943
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    • 1993
  • In this paper, robust recognition system for tilted facial image was developed. At first, standard facial image and lilted facial image are captured by CCTV camera and then transformed into binary image. The binary image is processed in order to obtain contour image by Laplacian edge operator. We trace and delete outermost edge line and use inner contour lines. We label four inner contour lines in order among the inner lines, and then we extract left and right eye with known distance relationship and with two eyes coordinates, and calculate slope information. At last, we rotate the tilted image in accordance with slope information and then calculate the ten distance features between element and element. In order to make the system invariant to image scale, we normalize these features with distance between left and righ eye. Experimental results show 88% recognition rate for twenty five face images when tilted degree is considered and 60% recognition rate when tilted degree is not considered.

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A Study on Clustering and Color Difference Evaluation of Color Image using HSV Color Space (HSV색공간을 이용한 칼라화상의 클러스터링 및 색차평가에 관한 연구)

  • Kim, Young-Il
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.2
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    • pp.20-27
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    • 1998
  • This paper describes color clustering method based on color difference in the uniform Munsell color space obtained from hue, saturation, and value. The proposed method operates in the uniform HSV color space which is approximated using ${L^*}{a^*}{b^*}$ coordinate system based on the RGB inputs. A clustering and color difference evaluation are proposed by thresholding NBS unit which is likely to Balinkin color difference equation. Region segmentation and isolation process are carried out ISO DATA algorithm which is a self iterative clustering technique. Through the clustering of 2 input images according to the threshold value, satisfactory results are obtained. So, in conclusion, it is possible to extract result of better region segmentation using human color perception of the objects.

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Super-Pixel-Based Segmentation and Classification for UAV Image (슈퍼 픽셀기반 무인항공 영상 영역분할 및 분류)

  • Kim, In-Kyu;Hwang, Seung-Jun;Na, Jong-Pil;Park, Seung-Je;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.18 no.2
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    • pp.151-157
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    • 2014
  • Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

A Study on Fast Datum Transformation model for GIS (지리정보시스템을 위한 고속 측지계 변환 모델 연구)

  • Suh, Yong-Cheol
    • Journal of the Korean Association of Geographic Information Studies
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    • v.7 no.3
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    • pp.48-56
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    • 2004
  • This research focuses on the development of a fast datum transformation model to be used in GIS that utilizes real-time data transformation. Instance, when a GIS data constructed according to a datum is conformed to another datum, instead of transforming the axes of the original data, the data is transformed right before the results are reflected on the monitor. In this research, the prospects of calculating transformation parameters for every grid cells on the area based on two-dimensional conformal transformation model in order to decrease real-time datum transformation time while maintaining a high accuracy has been investigated. Research results showed that for a fixed area, the accuracies of the two-dimensional conformal transformation and the three-dimensional datum transformation, which requires more computing time, were almost equal and fast transformation speed, high accuracy real-time datum transformation is made feasible by implementing the grid-divided two-dimensional conformal transformation model.

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Slant Estimation and Correction for the Off-Line Handwritten Hangul String Using Hough transform (Hough 변환을 이용한 오프라인 필기 한글 문자열의 기울기 추정 및 교정)

  • 이성환;이동준
    • Korean Journal of Cognitive Science
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    • v.4 no.1
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    • pp.243-260
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    • 1993
  • This paper presents an efficient method for estimationg and correcting the slant of off-line handwritten Hangul strings.In the proposed method,after extracting contours from input image.Hough tranform is applied to the contours to detect lines and estimate slants of the lines.When Hough trans form is applied to the contours,pixels which are not parts of the same stroke could be detected as a line.In order to exclude these lines from slant estimation process,detected lines which have the length less than threshold are eliminated.Experiments have been performed with address images which were extracted from live envelopes provided by Seoul Mail Center.Experimental results show that the proposed method is superior to the previous methods,which had been done with handwritten English strings.in estimation the slant of off-line handwritten Hangul strings.

Personal Verification using Feature Patterns of Palmprint (손바닥 특징패턴을 이용한 개인식별)

  • 전선배;임영도
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.12
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    • pp.1437-1450
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    • 1992
  • This paper describes the feature extraction of the interdigital regions of palm, and proposes a personal verification algorithm using the extracted features and the pattern types of those. The procedures of the feature extraction are as follows : first, the interdigital region is partitioned into several subregions, examining the phase of rigdes in each subregion, deciding the direction of that phase, and making the direction matrix of the region, we analyze this direction matrix to contain a feature pattern, and then, yield the first core. Second, applying the thinning to around the first core and tracing the thinned ridges, we yield the feature pattern types and second cores. Finally, the feature patterns coordinates included all of them are built. Then, distances and directions from each second core reaching to all the others are yielded from that coordinates. These informations are used to make a feature parameter. In our verification algorithm, such pattern types, the numbers of feature patterns, theses positions and feature parameters are used to analyze.

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Resistivity Tomography in an Inclined Borehole to Surface Purvey Using a Pole-dipole Array (단극-쌍극자 배열을 이용한 경사시추공-지표 탐사에서 전기비저항 토모그래피)

  • Park Jong-Oh;Kim Hee-Joon;Park Chung-Hwa
    • The Journal of Engineering Geology
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    • v.16 no.3 s.49
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    • pp.255-263
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    • 2006
  • In an electrical tomographic survey using an inclined borehole with a pole-dipole array, we must consider several factors: a singular point associated with zero potential difference, a spatial discrepancy between electrode and nodal point in a model due to a inclined borehole, and a variation of geometric factors in connection with a irregular topography. Singular points which are represented by the normal distance from current source to the ground surface can be represented by serveral regions due to a irregular topography of ground surface. The method of element division can be applied to the region in which the borehole is curved, inclined or the distance between the electrodes is shorter than that of nodal points, because the coordinate of each electrode cannot be assigned directly to the nodal point if several electrodes are in an element. Test on a three-dimensional (3-D) synthetic model produces good images of conductive target and shoves stable convergence.

A 3D Face Modeling Method Using Region Segmentation and Multiple light beams (지역 분할과 다중 라이트 빔을 이용한 3차원 얼굴 형상 모델링 기법)

  • Lee, Yo-Han;Cho, Joo-Hyun;Song, Tai-Kyong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.70-81
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    • 2001
  • This paper presents a 3D face modeling method using a CCD camera and a projector (LCD projector or Slide projector). The camera faces the human face and the projector casts white stripe patterns on the human face. The 3D shape of the face is extracted from spatial and temporal locations of the white stripe patterns on a series of image frames. The proposed method employs region segmentation and multi-beam techniques for efficient 3D modeling of hair region and faster 3D scanning respectively. In the proposed method, each image is segmented into face, hair, and shadow regions, which are independently processed to obtain the optimum results for each region. The multi-beam method, which uses a number of equally spaced stripe patterns, reduces the total number of image frames and consequently the overall data acquisition time. Light beam calibration is adopted for efficient light plane measurement, which is not influenced by the direction (vertical or horizontal) of the stripe patterns. Experimental results show that the proposed method provides a favorable 3D face modeling results, including the hair region.

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Warping of 2D Facial Images Using Image Interpolation by Triangle Subdivision (삼각형 반복분할에 의한 영상 보간법을 활용한 2D 얼굴 영상의 변형)

  • Kim, Jin-Mo;Kim, Jong-Yoon;Cho, Hyung-Je
    • Journal of Korea Game Society
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    • v.14 no.2
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    • pp.55-66
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    • 2014
  • Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments.