• Title/Summary/Keyword: 속도 영상화

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Efficient DSM-CC Carousel Parsing and Cache Management Strategy in D-TV (데이터 방송의 효율적인 DSM-CC 캐러셀 처리와 캐시 관리 전략)

  • Jang, Jin-Ho;Lee, Hyuk-joon;Kim, Jungsun
    • Annual Conference of KIPS
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    • 2009.04a
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    • pp.1090-1093
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    • 2009
  • 최근 혁신적으로 발전하고 있는 데이터 방송은 사용자를 만족시키기 위해 더 높은 품질의 영상과 음성은 물론 다양한 어플리케이션을 제공하고 있다. 이러한 어플리케이션은 DSM-CC 프로토콜에 의해 STB(Set-top Box)에 전송되는데 각각의 DTV 미들웨어에 따라 DSM-CC 프로토콜의 데이터 구조가 다르다. 그리고 방송 환경의 특성상 데이터를 놓치게 되면 한 Cycle을 기다려야 하는 문제가 발생한다. 또한 캐시 관리 전략에 따라 사용자가 원하는 어플리케이션의 응답 속도가 다르기 때문에 효율적인 캐시 관리 전략이 필요하다. 본 논문에서는 각 미들웨어에서 사용하는 DSM-CC 프로토콜의 차이점을 파악하여 변경이 필요한 부분은 모듈화해서 쉽게 확장 할 수 DSM-CC 처리 시스템을 제안했다. 또한, 어플리케이션을 실행시키기 위한 응답 시간을 줄이기 위해 사용자의 선호도와 사용 빈도수를 고려한 캐시 전략을 제안한다.

A study on improving the performance of face recognition system based on similarity (유사도 기반 얼굴인식 시스템 성능 향상 연구)

  • Na, Seong-Won;Lee, Sang-Hun;Yoon, Kyoung-Ro
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.315-317
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    • 2021
  • 최근 팬데믹으로 인해 다양한 산업에서 온라인화가 빠르게 진행되고 있다. 이러한 흐름에 따라 생체 신호를 이용한 로그인 시스템이나 자동 출결관리 시스템의 개발 또한 활발하게 연구되고 있다. 이에 본 논문에서는 생체 정보 중 얼굴을 이용하여 산업에서 도입 가능한 수준까지 얼굴인식 시스템의 성능을 향상 시키고자 한다. 우리는 성능향상을 위해 먼저 얼굴인식 시스템에서 성능 저하원인인 영상 속 얼굴 위치 및 각도 변화를 해결하고자 정면 얼굴 Capture 방법을 제안하였다. 두 번째로는 FRR 오류가 발생하면 추가적으로 정면얼굴을 추출하여 개인 인증을 다시 시도방법을 제안하였다. 검증을 위해 얼굴인식 분야에서 가장 많이 사용되고 있는 유사도 기반 프레임워크를 구현하여 제안한 성능향상 방법을 적용, 실험 하였으며 420명의 Database를 구축하고 2주 동안 99개의 비디오 데이터를 수집하여 실제 산업에서 도입 가능한 환경과 유사하게 구축해 우리의 제안 방법을 테스트 및 검증하였다.

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A System for the Improvement of Elderly Health to Classify Pose Using Smart Mirror (스마트 미러를 활용한 노인 건강 증진 자세 분류 시스템)

  • Kang, Young-Seo;Choi, Kyeong-Seo;Lee, Ga-Young;Joo, Jong-Wha J.
    • Annual Conference of KIPS
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    • 2022.11a
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    • pp.681-683
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    • 2022
  • 코로나 19 로 인해 사회적으로 활동 범위에 제약이 많아져 신체 노화가 진행중인 노년층의 심각한 운동 부족 현상 발생했다. 이에 따라 본 연구는 스마트 미러 트레이닝 프로그램의 범람 속에 신체적인 불편함을 가지고 있는 노인의 건강 증진에 주목하여 스마트 미러와 노인 자세 탐지, 자세 정확성 판단 시스템을 기반으로 한 자세 분류 서비스 제공 프로그램을 제안한다. 스마트 미러에 탑재된 카메라로 받아온 영상을 MoveNet 과 머신러닝 모델을 사용하여 사용자의 동작을 파악하는 방식으로 활동 프로그램을 진행한다. 향후 디지털 소외 계층의 사용 및 노인 자세 데이터 분석에 활용할 수 있을 것으로 기대한다.

Image Watermarking for Copyright Protection of Images on Shopping Mall (쇼핑몰 이미지 저작권보호를 위한 영상 워터마킹)

  • Bae, Kyoung-Yul
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.147-157
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    • 2013
  • With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.

A license plate area segmentation algorithm using statistical processing on color and edge information (색상과 에지에 대한 통계 처리를 이용한 번호판 영역 분할 알고리즘)

  • Seok Jung-Chul;Kim Ku-Jin;Baek Nak-Hoon
    • The KIPS Transactions:PartB
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    • v.13B no.4 s.107
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    • pp.353-360
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    • 2006
  • This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

Detecting Line Segment by Incremental Pixel Extension (점진적인 화소 확장에 의한 선분 추출)

  • Lee, Jae-Kwang;Park, Chang-Joon
    • Journal of Korea Multimedia Society
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    • v.11 no.3
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    • pp.292-300
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    • 2008
  • An algorithm for detecting a line segment in an image is presented using incremental pixel extension. We use a different approach from conventional algorithms, such as the Hough transform approach and the line segment grouping approach. The Canny edge is calculated and an arbitrary point is selected among the edge elements. After the arbitrary point is selected, a base line approximating the line segment is calculated and edge pixels within an arbitrary radius are selected. A weighted value is assigned to each edge pixel, which is selected by using the error of the distance and the direction between the pixel and the base line. A line segment is extracted by Jilting a line using the weighted least square method after determining whether selected pixels are linked or delinked using the sum comparison of the weights. The proposed algorithm is compared with two other methods and results show that our algorithm is faster and can detect the real line segment.

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Waveform inversion of shallow seismic refraction data using hybrid heuristic search method (하이브리드 발견적 탐색기법을 이용한 천부 굴절법 자료의 파형역산)

  • Takekoshi, Mika;Yamanaka, Hiroaki
    • Geophysics and Geophysical Exploration
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    • v.12 no.1
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    • pp.99-104
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    • 2009
  • We propose a waveform inversion method for SH-wave data obtained in a shallow seismic refraction survey, to determine a 2D inhomogeneous S-wave profile of shallow soils. In this method, a 2.5D equation is used to simulate SH-wave propagation in 2D media. The equation is solved with the staggered grid finite-difference approximation to the 4th-order in space and 2nd-order in time, to compute a synthetic wave. The misfit, defined using differences between calculated and observed waveforms, is minimised with a hybrid heuristic search method. We parameterise a 2D subsurface structural model with blocks with different depth boundaries, and S-wave velocities in each block. Numerical experiments were conducted using synthetic SH-wave data with white noise for a model having a blind layer and irregular interfaces. We could reconstruct a structure including a blind layer with reasonable computation time from surface seismic refraction data.

Illumination and Rotation Invariant Object Recognition (조명 영향 및 회전에 강인한 물체 인식)

  • Kim, Kye-Kyung;Kim, Jae-Hong;Lee, Jae-Yun
    • The Journal of the Korea Contents Association
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    • v.12 no.11
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    • pp.1-8
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    • 2012
  • The application of object recognition technology has been increased with a growing need to introduce automated system in industry. However, object transformed by noises and shadows appeared from illumination causes challenge problem in object detection and recognition. In this paper, an illumination invariant object detection using a DoG filter and adaptive threshold is proposed that reduces noises and shadows effects and reserves geometry features of object. And also, rotation invariant object recognition is proposed that has trained with neural network using classes categorized by object type and rotation angle. The simulation has been processed to evaluate feasibility of the proposed method that shows the accuracy of 99.86% and the matching speed of 0.03 seconds on ETRI database, which has 16,848 object images that has obtained in various lighting environment.

Design of FPGA-based Wearable System for Checking Patients (환자 체크를 위한 FPGA 기반 웨어러블 시스템 설계)

  • Kang, Sungwoo;Ryoo, Kwangki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.477-479
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    • 2017
  • With the recent advances in medical technology and health care, the prevention and treatment of diseases has developed. Accordingly aging has rapidly progressed. In this life span and aging society, demand for diagnostic centered medical care is increasing rapidly. In this paper, we propose a wearable patient check system based on FPGA that can be controlled by sensors. In the existing hospital, a doctor or nurse visited the patient every hour to check the condition. However, in this paper, patients, doctors and nurses can check the patient's condition at the desired time using patient check system. In addition, the tilt sensor is used for the patient who is uncomfortable to easily control. The proposed FPGA-based hardware architecture consists of an algorithm for enlarged image processing, a TFT-LCD Controller, a CIS Controller, and a Memory Controller to output the patient's status image. Implemented and validated using the DE2-115 test board with Cyclone IV EP4CE115F29C7 FPGA device and its operating frequency is 50MHz.

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Acceleration of CNN Model Using Neural Network Compression and its Performance Evaluation on Embedded Boards (임베디드 보드에서의 인공신경망 압축을 이용한 CNN 모델의 가속 및 성능 검증)

  • Moon, Hyeon-Cheol;Lee, Ho-Young;Kim, Jae-Gon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.44-45
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    • 2019
  • 최근 CNN 등 인공신경망은 최근 이미지 분류, 객체 인식, 자연어 처리 등 다양한 분야에서 뛰어난 성능을 보이고 있다. 그러나, 대부분의 분야에서 보다 더 높은 성능을 얻기 위해 사용한 인공신경망 모델들은 파라미터 수 및 연산량 등이 방대하여, 모바일 및 IoT 디바이스 같은 연산량이나 메모리가 제한된 환경에서 추론하기에는 제한적이다. 따라서 연산량 및 모델 파라미터 수를 압축하기 위한 딥러닝 경량화 알고리즘이 연구되고 있다. 본 논문에서는 임베디트 보드에서의 압축된 CNN 모델의 성능을 검증한다. 인공지능 지원 맞춤형 칩인 QCS605 를 내장한 임베디드 보드에서 카메라로 입력한 영상에 대해서 원 CNN 모델과 압축된 CNN 모델의 분류 성능과 동작속도 비교 분석한다. 본 논문의 실험에서는 CNN 모델로 MobileNetV2, VGG16 을 사용했으며, 주어진 모델에서 가지치기(pruning) 기법, 양자화, 행렬 분해 등의 인공신경망 압축 기술을 적용하였을 때 원래의 모델 대비 추론 시간 및 분류의 정확도 성능을 분석하고 인공신경망 압축 기술의 유용성을 확인하였다.

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