• Title/Summary/Keyword: Top-View Image

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Image processing for a top-view based parking assistance system (탑뷰 기반 주차 지원 시스템을 위한 영상처리)

  • Woo, Byung-Wook;Kim, Young-Joong;Kim, Jin-Hyung;Lee, Kwang-Wook;Hong, Min-Sun;Yoon, Shang-Moon;Park, Nam-Sook;Park, Geon-Kyu;Ko, Sung-Jea;Lim, Myo-Taeg
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.274-275
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    • 2008
  • 탑뷰 기반 주자 지원 시스템 (Top-View Based Parking Assistance System)은 차량의 전자장치 기술과 영상 기반 제어 기술을 융합하여 운전자들의 판단 및 조작 실수로 인한 경제적 손실이나 운전자들의 주차에 대한 중압감을 해소한다. 본 논문에서는 이를 구현하기 위하여 차량의 전, 후 좌, 우 네 위치에 카메라를 장착하였고 각 카메라의 높이 초점 거리, 렌즈의 종류와 지면에 대한 각 등을 공식화하여 영강-지면 좌표 모델을 개발하였다. 이를 바탕으로 추출된 영상을 확대, 축소, 회전, 조합 등의 영상처리를 이용하여 차량의 위에서 내려다보는 것과 같은 영상을 생성하는 알고리즘을 제안하고 VC++을 이용하여 소프트웨어 어플리케이션으로 개발하였다.

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An Image Processing System for Measuring the Weight of A Dairy Cattle (젖소 체중측정을 위한 영상처리 시스템)

  • 이대원;김현태
    • Journal of Animal Environmental Science
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    • v.7 no.3
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    • pp.183-190
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    • 2001
  • The objective of this research was to design and construct an image processing system to measure easily and accurately cow's weight. The image processing system was built for a dairy cattle to be measured and estimated it's weight using camera and personal computer. The pixel numbers, which was derived from the image processing system, were counted to estimate the weight of a dairy cattle. They were utilized various was for finding the relationships between pixel numbers and it's real weight. Based on the results of this research the following conclusions were made: 1. It's weight could be estimated by using pixel numbers, which was captured from top and side cameras to measure it. The correlations with tea-view pixel numbers, side-view pixel numbers, superficial area pixel numbers and the volume pixel numbers were 0.909, 0.939, 0.944 and 0.965. 2. 50 cattle was used to execute an experiment with the image processing system, but average errors were big to make out the good relationship between cow's weight and pixel numbers. In order measure accurately a cattle weight, cattle weight, cattle groups would be divided by the age of cattle and further study should be carried out to be based on the results of this research. 3. The average time it took to perform the image processing to be measure it was 10 seconds, but it took 10 minutes for cattle to enter for measuring it's weight into the weighting system.

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Deep Learning Similarity-based 1:1 Matching Method for Real Product Image and Drawing Image

  • Han, Gi-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.59-68
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    • 2022
  • This paper presents a method for 1:1 verification by comparing the similarity between the given real product image and the drawing image. The proposed method combines two existing CNN-based deep learning models to construct a Siamese Network. After extracting the feature vector of the image through the FC (Fully Connected) Layer of each network and comparing the similarity, if the real product image and the drawing image (front view, left and right side view, top view, etc) are the same product, the similarity is set to 1 for learning and, if it is a different product, the similarity is set to 0. The test (inference) model is a deep learning model that queries the real product image and the drawing image in pairs to determine whether the pair is the same product or not. In the proposed model, through a comparison of the similarity between the real product image and the drawing image, if the similarity is greater than or equal to a threshold value (Threshold: 0.5), it is determined that the product is the same, and if it is less than or equal to, it is determined that the product is a different product. The proposed model showed an accuracy of about 71.8% for a query to a product (positive: positive) with the same drawing as the real product, and an accuracy of about 83.1% for a query to a different product (positive: negative). In the future, we plan to conduct a study to improve the matching accuracy between the real product image and the drawing image by combining the parameter optimization study with the proposed model and adding processes such as data purification.

Analysis on the Importance of Beautiful Place Images Recognition Using AHP (AHP를 활용한 아름다운 장소 이미지의 중요도 인식 분석)

  • Lee, Lim-Jung;Cho, Chi-Woung;Noh, Kyung-Ran
    • Journal of the Korean Institute of Rural Architecture
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    • v.24 no.2
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    • pp.1-11
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    • 2022
  • Purpose: The purpose of this study is to analyze image factors of places located in natural and humanistically superior geographical locations. It aims to analyze image recognition and spatiality of scenically historical Sahmyook University, located northeast of Gangneung, through standardization. Method: The analysis method of landscape is composed of data investigation and research, and elements of how students, faculty, and visitors recognize a place's beautiful image will be examined. Result: A phenomenological approach was applied to how the images of beautiful place were set by FGI group meeting, and how such factors affect beautiful place's perception from the user's point of view. When looking at comprehensive ranking of image factors in recognition of beautiful landscapes, factors corresponding to forest landscapes appear at the top rank. In determining factors for its recognition, shared space with natural elements such as water, trees, flowers, etc. has been analyzed to have the biggest influence. Among factors corresponding to urban landscape, 'streets and pedestrian paths' is of medium importance and are recognized for it is artificial structure coexisting with natural elements shared with humans. The image corresponding to 'city area' and 'architecture' was analyzed to have insignificant influence on beautiful places' image recognition for artificial element was prioritized.

An User-Friendly Method of Image Warping for Traffic Monitoring System (실시간 교통상황 모니터링 시스템을 위한 유저 친화적인 영상 변형 방법)

  • Yi, Chuho;Cho, Jungwon
    • Journal of Digital Convergence
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    • v.14 no.12
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    • pp.231-236
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    • 2016
  • Currently, a traffic monitoring service using a surveillance camera is provided through internet. In general, if the user points a certain location on a map, then this service shows the real-time image of the camera where it is mounted. In this paper, we proposed the intuitive surveillance monitoring system which displays a real-time camera image on the map by warping with bird's-eye view and with the top of image as the north. In order to robustly estimate the road plane using camera image, we used the motion vectors which can be detected to changes in brightness. We applied a re-adjustment process to have the same directivity with a map and presented a user-friendly interface that can be displayed on the map. In the experiment, the proposed method was presented as the result of warping image that the user can easily perceive like a map.

Survey on Deep Learning-based Panoptic Segmentation Methods (딥 러닝 기반의 팬옵틱 분할 기법 분석)

  • Kwon, Jung Eun;Cho, Sung In
    • IEMEK Journal of Embedded Systems and Applications
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    • v.16 no.5
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    • pp.209-214
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    • 2021
  • Panoptic segmentation, which is now widely used in computer vision such as medical image analysis, and autonomous driving, helps understanding an image with holistic view. It identifies each pixel by assigning a unique class ID, and an instance ID. Specifically, it can classify 'thing' from 'stuff', and provide pixel-wise results of semantic prediction and object detection. As a result, it can solve both semantic segmentation and instance segmentation tasks through a unified single model, producing two different contexts for two segmentation tasks. Semantic segmentation task focuses on how to obtain multi-scale features from large receptive field, without losing low-level features. On the other hand, instance segmentation task focuses on how to separate 'thing' from 'stuff' and how to produce the representation of detected objects. With the advances of both segmentation techniques, several panoptic segmentation models have been proposed. Many researchers try to solve discrepancy problems between results of two segmentation branches that can be caused on the boundary of the object. In this survey paper, we will introduce the concept of panoptic segmentation, categorize the existing method into two representative methods and explain how it is operated on two methods: top-down method and bottom-up method. Then, we will analyze the performance of various methods with experimental results.

Forward Vehicle Movement Estimation Algorithm (전방 차량 움직임 추정 알고리즘)

  • Park, Han-dong;Oh, Jeong-su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.9
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    • pp.1697-1702
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    • 2017
  • This paper proposes a forward vehicle movement estimation algorithm for the image-based forward collision warning. The road region in the acquired image is designated as a region of interest (ROI) and a distance look up table (LUT) is made in advance. The distance LUT shows horizontal and vertical real distances from a reference pixel as a test vehicle position to any pixel as a position of a vehicle on the ROI. The proposed algorithm detects vehicles in the ROI, assigns labels to them, and saves their distance information using the distance LUT. And then the proposed algorithm estimates the vehicle movements such as approach distance, side-approaching and front-approaching velocities using distance changes between frames. In forward vehicle movement estimation test using road driving videos, the proposed algorithm makes the valid estimation of average 98.7%, 95.9%, 94.3% in the vehicle movements, respectively.

Transparent Manipulators Accomplished with RGB-D Sensor, AR Marker, and Color Correction Algorithm (RGB-D 센서, AR 마커, 색수정 알고리즘을 활용한 매니퓰레이터 투명화)

  • Kim, Dong Yeop;Kim, Young Jee;Son, Hyunsik;Hwang, Jung-Hoon
    • The Journal of Korea Robotics Society
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    • v.15 no.3
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    • pp.293-300
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    • 2020
  • The purpose of our sensor system is to transparentize the large hydraulic manipulators of a six-ton dual arm excavator from the operator camera view. Almost 40% of the camera view is blocked by the manipulators. In other words, the operator loses 40% of visual information which might be useful for many manipulator control scenarios such as clearing debris on a disaster site. The proposed method is based on a 3D reconstruction technology. By overlaying the camera image from front top of the cabin with the point cloud data from RGB-D (red, green, blue and depth) cameras placed at the outer side of each manipulator, the manipulator-free camera image can be obtained. Two additional algorithms are proposed to further enhance the productivity of dual arm excavators. First, a color correction algorithm is proposed to cope with the different color distribution of the RGB and RGB-D sensors used on the system. Also, the edge overlay algorithm is proposed. Although the manipulators often limit the operator's view, the visual feedback of the manipulator's configurations or states may be useful to the operator. Thus, the overlay algorithm is proposed to show the edge of the manipulators on the camera image. The experimental results show that the proposed transparentization algorithm helps the operator get information about the environment and objects around the excavator.

Automated Print Quality Assessment Method for 3D Printing AI Data Construction

  • Yoo, Hyun-Ju;Moon, Nammee
    • Journal of Information Processing Systems
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    • v.18 no.2
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    • pp.223-234
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    • 2022
  • The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

A Study on the Eco-friendly Kitchen Detergent Container Design (조선조 경상의 다리형태를 적용한 친환경 주방세제 용기디자인 연구)

  • Kim, Chung Ho
    • Journal of the Korea Furniture Society
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    • v.25 no.4
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    • pp.353-363
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    • 2014
  • Design of the container was designed to be able to have a sense of security by emphasizing the points and easy to use sophisticated in order to match the image of the company in an environmentally friendly form of the whole. The design of the natural detergent container, because the container itself is to prevent related bar closely with water, a slip, with an emphasis on the form of fish swim, looks the handle of the oval for the harmony of the entire container I was used to the point. The image extraction in the ordinary, you can design by applying the curve of streamlined feet of thin in order to emphasize the image of honest companies, oval fuselage top, easily without slipping and harmony of the image of the entire container in view of the functional aspects can grab to, which is designed to enter the interior. The design of the natural environment detergent container industry, it was incorporated as much as possible to the vessel and corporate image and sense of stability and the proportion of the overall shape, the basic concepts, the form on the productivity and functionality in the field of design, through the change and simplicity, with an emphasis on merchantability.

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