• Title/Summary/Keyword: Image-development

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Development of an Improved Geometric Path Tracking Algorithm with Real Time Image Processing Methods (실시간 이미지 처리 방법을 이용한 개선된 차선 인식 경로 추종 알고리즘 개발)

  • Seo, Eunbin;Lee, Seunggi;Yeo, Hoyeong;Shin, Gwanjun;Choi, Gyeungho;Lim, Yongseob
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.2
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    • pp.35-41
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    • 2021
  • In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

Precision comparison of 3D photogrammetry scans according to the number and resolution of images

  • Park, JaeWook;Kim, YunJung;Kim, Lyoung Hui;Kwon, SoonChul;Lee, SeungHyun
    • International journal of advanced smart convergence
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    • v.10 no.2
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    • pp.108-122
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    • 2021
  • With the development of 3D graphics software and the speed of computer hardware, it is an era that can be realistically expressed not only in movie visual effects but also in console games. In the production of such realistic 3D models, 3D scans are increasingly used because they can obtain hyper-realistic results with relatively little effort. Among the various 3D scanning methods, photogrammetry can be used only with a camera. Therefore, no additional hardware is required, so its demand is rapidly increasing. Most 3D artists shoot as many images as possible with a video camera, etc., and then calculate using all of those images. Therefore, the photogrammetry method is recognized as a task that requires a lot of memory and long hardware operation. However, research on how to obtain precise results with 3D photogrammetry scans is insufficient, and a large number of photos is being utilized, which leads to increased production time and data capacity and decreased productivity. In this study, point cloud data generated according to changes in the number and resolution of photographic images were produced, and an experiment was conducted to compare them with original data. Then, the precision was measured using the average distance value and standard deviation of each vertex of the point cloud. By comparing and analyzing the difference in the precision of the 3D photogrammetry scans according to the number and resolution of images, this paper presents a direction for obtaining the most precise and effective results to 3D artists.

Research on Competitiveness of Information and Telecommunication Industry Using Standard Patent: Focusing on trend and network analysis (표준특허를 활용한 정보통신산업 분야 경쟁력 분석: 트랜드 및 네트워크 분석을 중심으로)

  • Jeong, Myoung Sun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.534-541
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    • 2021
  • This study aims to establish an efficient future technology development strategy in the information and telecommunications industry by grasping related technology trends and fusion complexity through an analysis based on standard patents. Analyzing 1,983 patents related to the information and telecommunications industry identified the trends in major patent applicants and detailed technologies in the world. In addition, technology trends were investigated through keyword analysis to examine the degree of complexity in information and communications technology, confirming the direction of research in information technology. Electronic component and wireless communications fields have relatively few standard patents, but they are highly convergent with other industrial technologies. Computer information processes and communication and broadcasting technologies are highly related to each other, so they can be used as standard fusion technologies in standard patents. In addition, standardization activities in optical and image/sound devices are found to be high.

The feature of the 'Mun-yi-jae-do' artistic attitude in Chinese Animation from 1949 to 1966 (1949-1966년 중국 애니메이션에 나타난 '문이재도' 문예관의 특징)

  • Liu, Danya;Lee, Dong-hun
    • Journal of Communication Design
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    • v.65
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    • pp.70-81
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    • 2018
  • From 1949 to 1966, after the new China was established, in order to consolidate newborn regime and erect national image, "proletariat revolutionary education" had become the main way of literary and artistic creation in the new era. In this era, Chinese animation began to produce to form the characteristics of emphasizing the ideological expression and political education from 1949 to1966, but it also made people misunderstand that it was the results of comprehensive containment of Soviet literary thoughts and creative models. In fact, Regardless of the subject matter, narrative, and role, Chinese animations have inherited and developed the ideological characteristics of the "Mun-yi-jae-do" literary view, forming a creative style that is different from the Soviet "dogmatism." The characteristics of "revolutionary hero role", "mythological expression of revolutionary thought" and "unique storytelling narrative mode" in Chinese animation from 1949 to 1966 were the inheritance and development of the "hero role", "mythological story", and "art of storytelling" of the important expression means of traditional art creation after the establishment of the "Mun-yi-jae-do".

Development of Automatic Segmentation Algorithm of Intima-media Thickness of Carotid Artery in Portable Ultrasound Image Based on Deep Learning (딥러닝 모델을 이용한 휴대용 무선 초음파 영상에서의 경동맥 내중막 두께 자동 분할 알고리즘 개발)

  • Choi, Ja-Young;Kim, Young Jae;You, Kyung Min;Jang, Albert Youngwoo;Chung, Wook-Jin;Kim, Kwang Gi
    • Journal of Biomedical Engineering Research
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    • v.42 no.3
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    • pp.100-106
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    • 2021
  • Measuring Intima-media thickness (IMT) with ultrasound images can help early detection of coronary artery disease. As a result, numerous machine learning studies have been conducted to measure IMT. However, most of these studies require several steps of pre-treatment to extract the boundary, and some require manual intervention, so they are not suitable for on-site treatment in urgent situations. in this paper, we propose to use deep learning networks U-Net, Attention U-Net, and Pretrained U-Net to automatically segment the intima-media complex. This study also applied the HE, HS, and CLAHE preprocessing technique to wireless portable ultrasound diagnostic device images. As a result, The average dice coefficient of HE applied Models is 71% and CLAHE applied Models is 70%, while the HS applied Models have improved as 72% dice coefficient. Among them, Pretrained U-Net showed the highest performance with an average of 74%. When comparing this with the mean value of IMT measured by Conventional wired ultrasound equipment, the highest correlation coefficient value was shown in the HS applied pretrained U-Net.

Acceptance and Effectiveness of Distance Learning in Public Education in Saudi Arabia During Covid19 Pandemic: Perspectives from Students, Teachers and Parents

  • Alkinani, Edrees A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.54-65
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    • 2021
  • The movement control order and shutting down educational institution in Saudi Arabia has jeopardized the teaching and learning process. Education was shifted to distance learning in order to avoid any academic loss. In the middle of the Covid-19 crisis, there is a need to assess the full image of e-learning in Saudi Arabia. To investigate student and teachers' perception and acceptance, parents' attitudes and believes about distance education are the main goals of the study. The mix-method research design was employed to collect data. Three surveys were distributed to 100 students and 50 teachers and 50 parents from different educational institutions in Saudi Arabia, while semi-structured interviews were conducted with 10 parents. Random stratified and convenient sampling methods were adopted. Both descriptive and content analysis was conducted using SPSS25.0 and NVIVO software for quantitative and qualitative data accordingly. The findings showed that students are comfortable with remote education and are receiving enough support from schools and instructors but they think online education can't replace conventional face-to-face learning. Moreover, the results showed that teachers are having challenges in preparing online classes because of the development of conducting online classes and the lack of training. However, parents showed negative attitudes regarding the benefits and values of remote education and preferred conventional learning styles in elementary schools. Parents tended to reject and resist distance learning for several reasons: professional knowledge and lack of time to support their young kids in online classes, the shortcomings of e-learning, young children's inadequate self-regulation. Saudi parents are neither trained nor ready to use e-learning. The study provided suggestion and implications for teacher education and policymakers.

Development of Smart Tote Bags with Marquage Techniques Using Optical Fiber and LEDs (광섬유와 LED를 활용한 마카쥬(marquage) 기법의 스마트 토트백 개발)

  • Park, Jinhee;Kim, Sang Jin;Kim, Jooyong
    • Journal of Fashion Business
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    • v.25 no.1
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    • pp.51-64
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    • 2021
  • The purpose of this study was to develop smart bags that combining fashion-specific trends and smart information technologies such as light-emitting diodes(LED) and optic fibers by grafting marquage techniques that have recently become popular as part of eco-fashion. We applied e-textiles by designing leather tote bags that could show off LED luminescence. A total of two tote bags, a white-colored peacock design and a black-colored paisley design, divided the LED's light-emitting method into two types, incremental lighting and random light-emission to suit each design, and the locations of the optical fibers were also reversed depending upon the design. The production of circuits for the LEDs and optical fibers was based on the design, and a flexible conductive fabric was laser-cut instead of wire line and attached to the circuit-line location. A separate connector was underwent three-dimensional(3D)-modeling and was connected to high-luminosity LEDs and optic fiber bundles. The optical fiber logo part expressed a subtle image using a white-colored LED, which did not offset the LED's sharp luminous effects, suggesting that using LEDs with fiber optics allowed for the expression of each in harmony without being heterogeneous. Overall, the LEDs and fiber optic fabric were well-harmonized in the fashion bag using marquage techniques, and there was no sense of it being a mechanical device. Also, the circuit part was made of conductive fabric, which is an e-textile product that feels the same as a thin, flexible fabric. The study confirmed that the bag was developed as a smart wearable product that could be used in everyday life.

Conversion Program of Music Score Chord using OpenCV and Deep Learning (영상 처리와 딥러닝을 이용한 악보 코드 변환 프로그램)

  • Moon, Ji-su;Kim, Min-ji;Lim, Young-kyu;Kong, Ki-sok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.1
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    • pp.69-77
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    • 2021
  • This paper deals with the development of an application that converts the PDF music score entered by the user into a MIDI file of the chord the user wants. This application converts the PDF file into a PNG file for chord conversion when the user enters the PDF music score file and the chord which the user wants to change. After recognizing the melody of sheet music through image processing algorithm and recognizing the tempo of sheet music notes through deep learning, then the MIDI file of chord for existing sheet music is produced. The OpenCV algorithm and deep learning can recognize minim note, quarter note, eighth note, semi-quaver note, half rest, eighth rest, quarter rest, semi-quaver rest, successive notes and chord notes. The experiment shows that the note recognition rate of the music score was 100% and the tempo recognition rate was 90% or more.

Efficient Deep Neural Network Architecture based on Semantic Segmentation for Paved Road Detection (효율적인 비정형 도로영역 인식을 위한 Semantic segmentation 기반 심층 신경망 구조)

  • Park, Sejin;Han, Jeong Hoon;Moon, Young Shik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.11
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    • pp.1437-1444
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    • 2020
  • With the development of computer vision systems, many advances have been made in the fields of surveillance, biometrics, medical imaging, and autonomous driving. In the field of autonomous driving, in particular, the object detection technique using deep learning are widely used, and the paved road detection is a particularly crucial problem. Unlike the ROI detection algorithm used in general object detection, the structure of paved road in the image is heterogeneous, so the ROI-based object recognition architecture is not available. In this paper, we propose a deep neural network architecture for atypical paved road detection using Semantic segmentation network. In addition, we introduce the multi-scale semantic segmentation network, which is a network architecture specialized to the paved road detection. We demonstrate that the performance is significantly improved by the proposed method.

Development of X-Ray Array Detector Signal Processing System (X-Ray 어레이 검출 모듈 신호처리 시스템 개발)

  • Lim, Ik-Chan;Park, Jong-Won;Kim, Young-Kil;Sung, So-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.10
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    • pp.1298-1304
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    • 2019
  • Since the 9·11 terror attack in 2001, the Maritime Logistics Security System has been strengthened and required X-ray image for every imported cargos from manufacturing countries to United States. For scanning cargos, the container inspection systems use high energy X-rays for examination of contents of a container to check the nuclear, explosive, dangerous and illegal materials. Nowadays, the X-ray cargo scanners are established and used by global technologies for inspection of suspected cargos in the customs agency but these technologies have not been localized and developed sufficiently. In this paper, we propose the X-ray array detector system which is a core component of the container scanning system. For implementation of X-ray array detector, the analog and digital signal processing units are fabricated with integrated hardware, FPGA logics and GUI software for real-time X-ray images. The implemented system is superior in terms of resolution and power consumption compared to the existing products currently used in ports.