• 한국정보통신학회논문지
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• 제13권8호
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• pp.1601-1607
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• 2009

비전 시스템은 카메라를 통하여 획득한 이미지 정보를 캡쳐 후, 이를 분석하여 물체를 인식하는 것으로서, 차종 분류를 포함 한 다양한 산업현장에서 사용하고 있다. 이런 필요성으로 인하여 차종 분류를 위한 많은 연구가 이루어지고 있으나 복잡한 계산과정으로 인하여 처리 시간이 많이 소요되는 단점이 있다. 본 논문에서는 임베디드 시스템을 기반으로 하는 Vision Box를 설계하고 이를 사용한 차종인식 시스템을 제안하였다. 제안한 Vision Box의 성능을 자동차의 차종분류를 통한 사전 테스트 결과 최적 화된 환경 조건에서는 100%의 차종별 인식률을 보였으며, 조명 및 회전의 작은 변화에 따른 테스트에서 차종인식은 가능하였으나, 패턴점수가 낮아졌다. 제안한 Vision Box 시스템을 산업 현장에 적용한 결과 처리시간, 인식률 등에서 산업체의 요구 조건을 만족 할 수 있음을 확인할 수 일었다.

• 한국정보통신학회논문지
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• 제11권1호
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• pp.191-197
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• 2007

본 연구의 목적은 카메라를 통하여 획득한 이미지 정보를 캡쳐 후, 이를 분석하여 물체의 동작을 인식하는 Vision Box를 설계하는데 목적이 있다. 본 연구는 고객 즉, 사용자의 요구조건을 최대한 반영하여 구현하고자 하였다. 구현하고자 하는 Vision Box 시스템은 특별한 외부의 부가적인 센서를 사용하지 않고 카메라를 통하여 들어오는 화상 정보만을 분석하여 물체를 식별할 수 있도록 하였다. 그리고 PLC와의 통신과 원격지에서 Vision Box를 제어 할 수 있는 방법도 지원할 수 있도록 하였다. 본 연구에서 제안한 Vision Box의 성능을 자동차의 차종분류를 통한 성능분석 결과 최적화 된 환경조건에서는 100%의 차종별 인식률을 보였으며, 조명 및 잡음과 회전의 작은 변화에 따른 테스트에서 차종인식은 가능하였으나, 패턴점수가 낮아졌다. 따라서 제안한 Vision Box 시스템이 다양한 산업분야에 적용될 수 있을 것이라 생각된다.

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

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.89-93
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• 2009

Embedded systems are becoming more popular as many embedded platforms have become more affordable. It offers a compact solution for many different problems including computer vision applications. Texture classification can be used to solve various problems, and implementing it in embedded platforms will help in deploying these applications into the market. This paper proposes to deploy the texture classification algorithms onto the embedded computer vision (ECV) platform. Two algorithms are compared; grey level co-occurrence matrices (GLCM) and Gabor filters. Experimental results show that raw GLCM on MATLAB could achieves 50ms, being the fastest algorithm on the PC platform. Classification speed achieved on PC and ECV platform, in C, is 43ms and 3708ms respectively. Raw GLCM could achieve only 90.86% accuracy compared to the combination feature (GLCM and Gabor filters) at 91.06% accuracy. Overall, evaluating all results in terms of classification speed and accuracy, raw GLCM is more suitable to be implemented onto the ECV platform.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 추계학술발표대회
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• pp.80-83
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• 2019

지능형 로봇 기술은 더 나은 생활을 위한 현대 기술의 집약체이다. 산업, 생활, 정밀 기술 등 다양한 분야에서 응용이 가능한 확장성 넓은 분야이다. 해당 분야의 추적 기술은 LIDAR를 활용하는 방향으로 활발한 연구가 진행 중이다. LIDAR는 사방의 거리를 정확하게 측정할 수 있는 유용한 센서지만, LIDAR만으로는 로봇의 성능을 최대화할 수는 없다. 본 논문은 LIDAR 추적을 연장하여 Vision 기술의 융합에 관련하여 서술한다. Vision 기술의 융합을 통한 향상된 기능을 가지는 추적 로봇 설계 방법을 제안한다.

• 반도체디스플레이기술학회지
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• 제15권1호
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• pp.47-51
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• 2016

Human visual system infers 3D vision through stereo disparity in the stereoscopic images, and stereo visioning are recently being used in consumer electronics which has resulted in much research in the application field. Basically, stereo vision system consists of four processes, which are cost computation, cost aggregation, disparity calculation, and disparity refinement. In this paper, we present and evaluate the existing various methods, focusing on cost aggregation for stereo vision system to comparatively analyze the performance of their algorithms for a given set of resources. Experiments show that Normalized Cross Correlation and Zero-Mean Normalized Cross Correlation provide higher accuracy, however they are computationally heavy for embedded system in the real time systems. Sum of Absolute Difference and Sum of Squared Difference are more suitable selection for embedded system, but they should be required on improvement to apply to the real world system.

• 대한임베디드공학회논문지
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• 제3권3호
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.116.4-116
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• 2002

$\textbullet$In case of using overhead camera system, mobile robot moves under static working area. $\textbullet$Mobile robot must use onboard camera system to work under wide working area. $\textbullet$Mobile robot must have wireless LAN to remove restriction of movement. $\textbullet$Onboard camera system must have wireless LAN environment. $\textbullet$We develop embedded vision platform using onboard camera.

• 전자통신동향분석
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• 제36권2호
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• pp.56-64
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• 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.

• 대한임베디드공학회논문지
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• 제10권2호
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• pp.101-108
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• 2015

In this paper, a robust traffic light detection method is proposed by using vision sensor and DGPS(Difference Global Positioning System). The conventional vision-based detection methods are very sensitive to illumination change, for instance, low visibility at night time or highly reflection by bright light. To solve these limitations in visual sensor, DGPS is incorporated to determine the location and shape of traffic lights which are available from traffic light database. Furthermore the geometric relationship between traffic light and vision sensor is used to locate the traffic light in the image by using DGPS information. The empirical results show that the proposed method improves by 51% in detection rate for night time with marginal improvement in daytime environment.