• 전자통신동향분석
• /
• 제36권2호
• /
• pp.56-64
• /
• 2021

Many computer vision algorithms are computationally expensive and require a lot of computing resources. Recently, owing to machine learning technology and high-performance embedded systems, vision processing applications, such as object detection, face recognition, and visual inspection, are widely used. However, on-devices need to use their resources to handle powerful vision works with low power consumption in heterogeneous environments. Consequently, global manufacturers are trying to lock many developers into their ecosystem, providing integrated low-power chips and dedicated vision libraries. Khronos Group-an international standard organization-has released the OpenVX standard for high-performance/low-power vision processing in heterogeneous on-device systems. This paper describes vision libraries for the embedded systems and presents the OpenVX standard along with related trends for on-device vision system.

• ETRI Journal
• /
• 제27권5호
• /
• pp.539-544
• /
• 2005

An analog CMOS vision chip for edge detection with power consumption below 20mW was designed by adopting electronic switches. An electronic switch separates the edge detection circuit into two parts; one is a logarithmic compression photocircuit, the other is a signal processing circuit for edge detection. The electronic switch controls the connection between the two circuits. When the electronic switch is OFF, it can intercept the current flow through the signal processing circuit and restrict the magnitude of the current flow below several hundred nA. The estimated power consumption of the chip, with $128{\times}128$ pixels, was below 20mW. The vision chip was designed using $0.25{\mu}m$ 1-poly 5-metal standard full custom CMOS process technology.

• 대한임베디드공학회논문지
• /
• 제8권1호
• /
• pp.25-29
• /
• 2013

Recently ARM processor's processing power has been increasing rapidly as it has been applied to consumer electronics products. Because of its computing power and low power consumption, it is used to various embedded systems.( including vision processing systems.) Embedded linux that provides well-made platform and GUI is also a powerful tool for ARM based embedded systems. So short period to develop is one of major advantages to the ARM based embedded system. However, for real-time date processing applications such as an image processing system, ARM needs additional equipments such as FPGA that is suitable to parallel processing applications. In this paper, we developed an embedded system using ARM processor and FPGA. FPGA takes time consuming image preprocessing and numerical algorithms needs floating point arithmetic and user interface are implemented using the ARM processor. Overall processing speed of the system is 60 frames/sec of VGA images.

• 한국정보기술응용학회:학술대회논문집
• /
• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
• /
• pp.285-288
• /
• 2005

We propose a novel programmable miniature vision module based on a custom designed analog VLSI (aVLSI) chip. The vision module consists of the optical flow vision sensor embedded with commercial off-the-shelves digital hardware; in our case is the Intel XScale PXA270 processor enforced with a programmable gate array device. The aVLSI sensor provides gray-scale imager data as well as smooth optical flow estimates, thus each pixel gives a triplet of information that can be continuously read out as three independent images. The particular computational architecture of the custom designed sensor, which is fully parallel and also analog, allows for efficient real-time estimations of the smooth optical flow. The Intel XScale PXA270 controls the sensor read-out and furthermore allows, together with the programmable gate array, for additional higher level processing of the intensity image and optical flow data. It also provides the necessary standard interface such that the module can be easily programmed and integrated into different vision systems, or even form a complete stand-alone vision system itself. The low power consumption, small size and flexible interface of the proposed vision module suggests that it could be particularly well suited as a vision system in an autonomous robotics platform and especially well suited for educational projects in the robotic sciences.

• 대한원격탐사학회지
• /
• 제4권1호
• /
• pp.31-40
• /
• 1988

Low-cost microcomputer systems can be assembled which possess computing power, color display, memory, and storage capacity approximately equal to graphic workstactions. A low-cost, flexible, and user-friendly IBM/PC/XT/AT based image processing system has been developed and named as KMIPS(KAIST (Korea Advanced Institute of Science & Technology) Map and Image Processing Station). It can be easily utilized by the resource managers who are not computer specialists. This system can: * directly access Landsat MSS and TM, SPOT, NOAA AVHRR, MOS-1 satellite imagery and other imagery from different sources via magnetic tape drive connected with IBM/PC; * extract image up to 1024 line by 1024 column and display it up to 480 line by 672 column with 512 colors simultaneously available; * digitize photographs using a frame grabber subsystem(512 by 512 picture elements); * perform a variety of image analyses, GIS and terrain analyses, and display functions; and * generate map and hard copies to the various scales. All raster data input to the microcomputer system is geographically referenced to the topographic map series in any rater cell size selected by the user. This map oriented, georeferenced approach of this system enables user to create a very accurately registered(.+-.1 picture element), multivariable, multitemporal data sets which can be subsequently subsequently subjected to various analyses and display functions.

• 한국정보전자통신기술학회논문지
• /
• 제13권6호
• /
• pp.568-574
• /
• 2020

본 논문에서는 영상처리에 사용되는 Canny edge 검출 알고리즘 중 가장 높은 연산 복잡도를 가진 제곱근 연산 횟수를 감소시키는 방법을 제안한다. 제안하는 방법은 기울기 벡터 연산 과정에 사용되는 제곱근 연산을 이용할 때 일부 픽셀에 특정한 규칙을 사용해 홀을 만들어 제곱근 연산을 직접 하지 않고 주변 픽셀들의 연속성을 이용하여 기울기 벡터를 계산하여 연산 횟수를 감소시킨다. 다양한 테스트 이미지를 이용해 실험한 결과 홀이 1개인 경우 약 97%, 홀을 증가시키면 각각 약 94%, 90%, 88%의 일치율을 보였고, 홀이 1개인 경우에는 0.2ms의 연산시간이 감소되었고, 홀을 증가시키면 각각 약 0.398ms 0.6ms, 0.8ms의 연산시간이 감소되었다. 이를 바탕으로 hole이 2개인 경우 높은 정확도와 연산 수 절감을 통해 저전력 임베디드 비전 시스템을 구현할 수 있을 것으로 기대한다.

• 센서학회지
• /
• 제30권1호
• /
• pp.15-19
• /
• 2021

Image processing is one of the major techniques that are used for computer vision. Nowadays, researchers are using machine learning and deep learning for the aforementioned task. In recent years, digit recognition tasks, i.e., automatic meter recognition approach using electric or water meters, have been studied several times. However, two major issues arise when we talk about previous studies: first, the use of the deep learning technique, which includes a large number of parameters that increase the computational cost and consume more power; and second, recent studies are limited to the detection of digits and not storing or providing detected digits to a database or mobile applications. This paper proposes a system that can detect the digital number of meter readings using a lightweight deep neural network (DNN) for low power consumption and send those digits to an Android mobile application in real-time to store them and make life easy. The proposed lightweight DNN is computationally inexpensive and exhibits accuracy similar to those of conventional DNNs.

• 전자통신동향분석
• /
• 제34권4호
• /
• pp.15-22
• /
• 2019

Recent technological advances in three-dimensional (3D) sensing devices and machine learning such as deep leaning has enabled data-driven 3D applications. Research on artificial intelligence has developed for the past few years and 3D deep learning has been introduced. This is the result of the availability of high-quality big data, increases in computing power, and development of new algorithms; before the introduction of 3D deep leaning, the main targets for deep learning were one-dimensional (1D) audio files and two-dimensional (2D) images. The research field of deep leaning has extended from discriminative models such as classification/segmentation/reconstruction models to generative models such as those including style transfer and generation of non-existing data. Unlike 2D learning, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become increasingly popular owing to advances in 3D vision technology, the generation/acquisition of 3D data is still very difficult. Even if 3D data can be acquired, post-processing remains a significant problem. Moreover, it is not easy to directly apply existing network models such as convolution networks owing to the various ways in which 3D data is represented. In this paper, we summarize technological trends in AI-based 3D content generation.

• 한국정보통신학회논문지
• /
• 제25권7호
• /
• pp.962-970
• /
• 2021

대부분의 자동차 사고는 졸음운전과 같은 운전자의 부주의로 인해 발생한다. 전방 추돌 경보 시스템 (FCWS)은 전방 차량으로부터 추돌 위험을 감지하여 운전자에게 사전에 경고함으로써 사고의 위험을 현저하게 줄여준다. 본 논문은 주행 안전을 위한 저전력 임베디드 기반 FCWS를 소개한다. 단일 카메라로부터 전방 차량에 대해 검출, 추적, 거리를 계산하고 현재 차량의 속도 정보를 통해 충돌시간 (TTC)을 계산한다. 또한 저성능 임베디드 시스템에서 실시간으로 동작하기 위해 높고 낮은 수준의 프로그램 최적화 기법을 소개한다. 이 시스템은 임베디드 시스템에서 사전에 취득해둔 주행 영상을 통해서 테스트 하였다. 최적화 기법을 사용한 결과는 이전에 최적화를 하지 않은 프로세스 보다 실행 시간이 약 170배 향상되었다.

• 인터넷정보학회논문지
• /
• 제21권2호
• /
• pp.9-18
• /
• 2020

영상 처리 기법을 이용한 영상 인식 분야는 버스 승차 및 하차 시에 승객을 움직이는 객체로 검출하고 개수하는 방법이 연구되고 있다. 이러한 기술 중에는 인공지능 기법의 하나인 딥러닝 기법이 사용되고 있다. 또 다른 방법으로 스테레오 비전 카메라를 이용하여 객체를 검출하는 방법도 사용되고 있다. 그러나 이러한 방법들은 객체를 검출할 때 사용되는 장비의 연산량이 많이 들어 고가의 하드웨어 장비가 필요하다. 그러나 대중교통 중 하나인 버스 승객을 검출하기 위해 상대적으로 연산량이 적은 기법을 이용하여 다양한 장비에 맞는 영상 처리 기술이 필요하다. 이에 본 논문에서는 다양한 장비에 맞는 이동 객체 검출 기법 중 배경 제거를 통한 객체의 윤곽선을 검출하여 대중교통 중의 하나인 버스에 탑승객의 수를 효율적으로 획득 할 수 있는 기법을 제안한다. 실험 결과 스테레오 비전을 장착한 장비보다 더 저사양의 장비에서 약 70%의 정확도로 승객을 개수하였다.