• 제목/요약/키워드: Range Segmentation

검색결과 184건 처리시간 0.03초

LiDAR 기반 차량-인프라 연계 상황인지를 통한 사고다발지역에서의 차량 종방향 능동제어 시스템 연구 (Research of Vehicles Longitudinal Adaptive Control using V2I Situated Cognition based on LiDAR for Accident Prone Areas)

  • 김재환;이제욱;윤복중;박재웅;김정하
    • 제어로봇시스템학회논문지
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    • 제18권5호
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    • pp.453-464
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    • 2012
  • This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

흑백영상처리장치를 이용한 과실선별기 개발에 관한 연구(I) - 크기 및 색택 판정 - (Development of a Fruit Grader using Black/White Image Processing System(I) - Determining the Size and Coloration -)

  • 노상하;이종환;이승훈
    • Journal of Biosystems Engineering
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    • 제17권4호
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    • pp.354-362
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    • 1992
  • This study was intended to examine feasibility of sizing and color grading of Fuji apple with black/white image processing system, to develop a device with which the whole surface of an apple could be captured by one camera, and to develop an algorithm for a high speed sorting. The results are summarized as follows : 1. The black/white image processing system used in this study showed a maximum error of 1.3% in area measurement with a reference figure while the focusing point of camera and location of the reference figure were changed within a certain range. 2. As the result of evaluating four automatic image segmentation algorithms with apple images, Histogram Clustering Method was the best in terms of computation time and accuracy. 3. The fast algorithm for analyzing size and coloration of apple was developed. 4. The whole surface of an apple could be captured in an image frame with two mirrors installed on the both sides of the sample. The total area of the image representing the whole surface showed a correlation of 0.995 with the weight of apple. 5. The gray level when a particular band pass filter was mounted on the camera showed high correlation with 'L' and 'a' values of Hunt color scale and could represent the coloration of apple.

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A Traffic Adaptive MAC Scheduling for Bluetooth with Maximized throughput and Guaranteed fairness

  • Kim Tae suk;Choi Sung-Gi;Kim Sehun
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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    • pp.418-425
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    • 2002
  • Bluetooth is an emerging technology expected to provide users with short range, low cost, pico-cellular wireless connectivity. The access to the medium for Bluetooth is based on a Master driven Time Division Duplexing (TDD) scheme. A slave transmits packets in the reverse slot only after the master polls the slave (or transmits a packet to the slave) in a forward slot. The master transmits packets to a slave in even slots while the slave transmits packets to the master in an odd slot. The way in which the master schedules packets transmission to slaves or polls them determines system performance. In this paper. we propose a traffic adaptive MAC scheduling scheme for Bluetooth. The proposed scheme adopts the ISAR (Intelligent Segmentation and Reassembly) policy, which adjusts the packet size to the traffic patterns, to adapt the polling frequency to the traffic conditions. Also for achieving fairness among master-slave connections our scheme includes a priority policy assinging prioritised service tlimes to each connection. By considering a scenario where a Bluetooth master is used as wireless access point to the Internet, we show that our scheme improve the system throughput and average queue delay with regard to a naive Round Robin (RR) scheme.

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An Adaptive Utterance Verification Framework Using Minimum Verification Error Training

  • Shin, Sung-Hwan;Jung, Ho-Young;Juang, Biing-Hwang
    • ETRI Journal
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    • 제33권3호
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    • pp.423-433
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    • 2011
  • This paper introduces an adaptive and integrated utterance verification (UV) framework using minimum verification error (MVE) training as a new set of solutions suitable for real applications. UV is traditionally considered an add-on procedure to automatic speech recognition (ASR) and thus treated separately from the ASR system model design. This traditional two-stage approach often fails to cope with a wide range of variations, such as a new speaker or a new environment which is not matched with the original speaker population or the original acoustic environment that the ASR system is trained on. In this paper, we propose an integrated solution to enhance the overall UV system performance in such real applications. The integration is accomplished by adapting and merging the target model for UV with the acoustic model for ASR based on the common MVE principle at each iteration in the recognition stage. The proposed iterative procedure for UV model adaptation also involves revision of the data segmentation and the decoded hypotheses. Under this new framework, remarkable enhancement in not only recognition performance, but also verification performance has been obtained.

Featured-Based Registration of Terrestrial Laser Scans with Minimum Overlap Using Photogrammetric Data

  • Renaudin, Erwan;Habib, Ayman;Kersting, Ana Paula
    • ETRI Journal
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    • 제33권4호
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    • pp.517-527
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    • 2011
  • Currently, there is a considerable interest in 3D object reconstruction using terrestrial laser scanner (TLS) systems due to their ability to automatically generate a considerable amount of points in a very short time. To fully map an object, multiple scans are captured. The different scans need to be registered with the help of the point cloud in the overlap regions. To guarantee reliable registration, the scans should have large overlap ratio with good geometry for the estimation of the transformation parameters among these scans. The objective of this paper is to propose a registration method that relaxes/eliminates the overlap requirement through the utilization of photogrammetrically reconstructed features. More specifically, a point-based procedure, which utilizes non-conjugate points along corresponding linear features from photogrammetric and TLS data, will be used for the registration. The non-correspondence of the selected points along the linear features is compensated for by artificially modifying their weight matrices. The paper presents experimental results from simulated and real datasets to illustrate the feasibility of the proposed procedure.

일본 여대생의 라이프스타일과 의류구매행동에 관한 연구 (A Study on the Japanese University Students' Clothing Buying Behavior according to Their Lifestyle)

  • 이옥희;김진경
    • 한국의류학회지
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    • 제29권2호
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    • pp.298-306
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    • 2005
  • The Main objective of this study was to investigate the relationship between lifestyle and clothing buying behavior of college female students in Japan. A questionnaire was developed to measure clothing urchasing motives, fashion information sources, evaluation criteria of clothing, store attribute and lifestyle, The questionnaire was administered to 131 female college students in Tokyo of Japan. the data was analyzed using percentage, frequency, mean, factor analysis, Cluster Analysis and ANOVA, Duncan Multiple Range test. The results of the study were as follows : 1. The female college students were classified into fourth subdivisions by the cluster analysis; rational group, economic group, progressive group, fashion-oriented group. 2. The clothing purchasing motives o consumers were significantly different according to lifestyle subdivision in social, personal. 3. In the case of fshion information sources, significant differences were found according to lifestyle subdivision in mass media information, information by marketer, information by consumer. 4. The evaluation criteria of clothing were significantly different depending on lifestyle subdivision in esthetic, quality and management, external criterion. 5. The store attribute were significantly different depending on lifestyle subdivision in convenience, service and atmosphere of store.

Building DSMs Generation Integrating Three Line Scanner (TLS) and LiDAR

  • Suh, Yong-Cheol;Nakagawa , Masafumi
    • 대한원격탐사학회지
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    • 제21권3호
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    • pp.229-242
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    • 2005
  • Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.

Deep Learning in MR Image Processing

  • Lee, Doohee;Lee, Jingu;Ko, Jingyu;Yoon, Jaeyeon;Ryu, Kanghyun;Nam, Yoonho
    • Investigative Magnetic Resonance Imaging
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    • 제23권2호
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    • pp.81-99
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    • 2019
  • Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.

전지형 크레인의 인양물 충돌방지를 위한 환경탐지 센서 시스템 개발 (Collision Avoidance Sensor System for Mobile Crane)

  • 김지철;김영재;김민극;이한민
    • 드라이브 ㆍ 컨트롤
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    • 제19권4호
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    • pp.62-69
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    • 2022
  • Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.

소비자의 라이프스타일에 따른 서비스품질 지각 차이에 관한 연구 (A Study on the Consumer's Service Quality Perception Based on the Types of Life-style)

  • 박윤서;이승인;최인
    • 마케팅과학연구
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    • 제19권2호
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    • pp.53-67
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    • 2009
  • For the last decades, service quality has been studied as one of the most important tools for a service company to compete with the other companies. Based on these past researches, it has been agreed that the service quality is a basic and powerful tool to create the competitive advantage. Due to similar reason, many service marketing practitioners have been also focused on the service quality to retain the existing consumers and collect the new consumers. However, service quality is subjectively perceived by individual consumers. Consumer evaluation of service quality can be different from each other. Especially consumers with one life-style may evaluate the service quality differently from the consumers with the other life-styles. Therefore we need to know whether there are differences in service quality perception on the categories of life-style. Life-style refers to a distinctive mode of living in its aggregate and broadest sense. It embodies the patterns that were developed and emerged from the dynamics of living in a society. Since the concept of life-style and its relationship to marketing was introduced in 1963 by William Lazer, methods of measuring the life-style and their application have been developed. Life-style has been usually used to segment the marketplace because it offers marketers a unique and important view of the market. When Life-style is combined with clustering methods, life-style segmentation can generate identifiable whole persons rather than isolated fragment. Life-style segmentation begins with people instead of products and classifies them into different life-style types, each characterized by a unique style of living based on a wide range of activities, interests, and opinions(Plummer, 1974). In this study we applies the life-style segmentation based on the AIO(Activities, Interests, and Opinions) to the consumers of the large discount stores. In Korea, the large discount store market has entered into maturity stage so that the market differentiation strategy is becoming a more critical issue to the marketing practitioners. One of the most important tools to differentiate from the competitors in large discount store market is continuously to provide service of better quality than competitors. This study tries to find answers about the following questions: 1) How can we categorize the consumer life-styles in the large discount store? 2) What are the characteristics of the categorized groups? 3) Are there any differences in service quality perception among the consumers with different life-styles 4) Are there any differences in consumer behavior among them in the large discount store? For the purpose, we collected survey data from consumers and analyzed the data with the SPSS package where we had $X^2$-test, factor analysis, ANOVA, MANOVA, and cluster analysis. The survey was made during one month in the April of 2008. Among the collected 306 copies of questionnaires, 281 copies were chosen as the effective samples for empirical analysis except 25 copies with wrong responses. To identify the life-style patterns, we used the measures employed by Kim and Kwon(1999), where 44 items on a seven-point scale were used to measure factors of the life-style patterns. The Principal Component Method was used for factor extraction, and the VARIMAX orthogonal factor rotation was employed. The 7 items showing low factor loading were eliminated. The results of the factor analysis suggested that nine factors of the life-style patterns were identified as follows: 1) the equality-of-sexes and pursuit-of-independence tendency 2) self-management tendency 3) sociable tendency 4) self-display tendency 5) degree of a dilettante life 6) pursuit-of-information tendency 7) bargain hunter tendency 8) TV preference tendency 9) pursuit-of-leisure tendency. Next, after the K-means cluster analysis was performed with nine factors of the life-style patterns, the life-styles of the respondents were classified into four groups which are named as the 'progressive practicality-oriented group', 'positive success-oriented group', 'sociable ostentation-oriented group', 'stable conservation-oriented group'. The analysis results for usage behavior between the market segments showed statistically significant differences in the frequency of usage, duration time in the store, consumer satisfaction, and loyalty. Also, we tried to investigate whether the large discount store consumers differently perceive the quality of service based upon the types of life-style. To measure the service quality of large discount store, we adapted several measurement models measuring the service quality such as SERVPERF, BCP, R-SERVPERF, R-BCP. MANOVA and One-Way ANOVA were performed to confirm the difference in service quality perception based on the market segments. The results have also shown significant differences between life-style types in service quality perception. These findings show that the large discount store marketers should consider consumer life-style as one of the most important market segments for marketing and understand the difference in service quality perception between life-style types. Our findings give important implications to marketers of large discount stores as well as life-style researchers. First, this study showed there were significant differences in consumer's service quality perception and usage behavior between the types of life-style. It provides evidence that the life-style approach can be a important basis in segmenting the large discount store market and will make consumers perceive the service quality high. Second, most previous researches on service quality have been in aggregate level. However, our results imply that the future research on service quality have to focus on segment level.

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