• 한국멀티미디어학회논문지
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• 제18권12호
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• pp.1453-1461
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• 2015

Since digital images and videos are rapidly increasing in the internet with the spread of mobile computers and smartphones, research on image retrieval has gained tremendous momentum. Color, shape, and texture are major features used in image retrieval. Especially, color information has been widely used in image retrieval, because it is robust in translation, rotation, and a small change of camera view. This paper proposes a new method for histogram refinement based on local color difference. Firstly, the proposed method converts a RGB color image into a HSV color image. Secondly, it reduces the size of color space from 256³ to 32. It classifies pixels in the 32-color image into three groups according to the color difference between a central pixel and its neighbors in a 3x3 local region. Finally, it makes a color difference vector(CDV) representing three refined color histograms, then image retrieval is performed by the CDV matching. The experimental results using public image database show that the proposed method has higher retrieval accuracy than other conventional ones. They also show that the proposed method can be effectively applied to search low resolution images such as thumbnail images.

• 한국멀티미디어학회논문지
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• 제15권8호
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• pp.986-995
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• 2012

본 논문에서는 스마트폰 카메라에서 움직이는 물체의 실시간 추적 방법을 제안한다. 사양이 낮은 플랫폼에서의 비-학습 기반 제약을 고려하여 히스토그램 특징 기반의 슬라이딩 윈도우 검출 기법을 사용한다. 각 부분 윈도우에 대한 히스토그램의 계산 시간문제는 적분 히스토그램을 통해 해결한다. 추가적인 속도개선과 성능향상을 위해 적응적 빈 방법을 제안한다. 자체 수집한 데이터에 대한 실험을 통해 우리는 초당 34~63프레임 수준의 높은 처리속도를 달성하였다.

• Journal of information and communication convergence engineering
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• 제13권4호
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (C)
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• pp.450-455
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• 2008

다시점 비디오는 여러 개의 시점(view-point)을 이용하여 현장감과 몰입감을 제공하는 새로운 형태의 멀티미디어 서비스이다. 시점의 개수가 증가함에 따라 방대한 양의 영상 데이터로 인한 영상 획득, 저장 전송 및 재현 시 문제가 발생한다. 또한 현재의 다시점 비디오에 관한 연구는 고정된 카메라로 환경이 제한되어 있다. 본 논문에서는 유동적인 카메라 환경에서 최적의 상관관계를 가지는 영상을 획득하기 위한 방법을 제안한다. 제안하는 방법은 영상의 일부분만을 선택하여 중복성을 먼저 측정하고, 중복성의 척도에 따라 사용자와의 상호작용을 통하여 높은 상관관계를 가지는 다시점 영상을 획득할 수 있다. 또한 영상 획득 시 카메라간의 조명 차이에 의해 발생되는 부정확성을 감소시키기 위해 영상 마스킹을 적용한다. 마스킹된 영상에 에지 검출 방법을 적용하여 변위 추정을 함으로써 계산 복잡도를 줄였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권2호
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• 한국생산제조학회지
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• 제22권3_1spc호
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• pp.607-614
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• 2013

This paper proposes a robot driving system and sensor implementation for use with an education robot. This robot has multiple functions and was designed so that children could use it with interest and ease. The robot recognizes the location of a user and follows that user at a specific distance when the robot and user communicate with each other. In this work, the robot was designed and manufactured to evaluate its performance. In addition, an embedded board was installed with the purpose of communicating with a smart phone, and a camera mounted on the robot allowed it to monitor the environment. To allow the robot to follow a moving user, a set of sensors combined with an RF module and ultrasonic sensors were adopted to measure the distance between the user and the robot. With the help of this ultrasonic sensors arrangement, the location of the user couldbe identified in all directions, which allowed the robot to follow the moving user at the desired distance. Experiments were carried out to see how well the user's location could be recognized and to investigate how accurately the robot trackedthe user, which eventually yielded a satisfactory performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.4103-4117
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• 2014

Image processing and computer vision algorithms are gaining larger concern in a variety of application areas such as robotics and man-machine interaction. Vision allows the development of flexible, intelligent, and less intrusive approaches than most of the other sensor systems. In this work, we determine the location and orientation of a mobile robot which is crucial for performing its tasks. In order to be able to operate in real time there is a need to speed up different vision routines. Therefore, we present and evaluate a method for introducing parallelism into the multiple non-overlapping camera pose estimation algorithm proposed in [1]. In this algorithm the problem has been solved in real time using multiple non-overlapping cameras and the Extended Kalman Filter (EKF). Four cameras arranged in two back-to-back pairs are put on the platform of a moving robot. An important benefit of using multiple cameras for robot pose estimation is the capability of resolving vision uncertainties such as the bas-relief ambiguity. The proposed method is based on algorithmic skeletons for low, medium and high levels of parallelization. The analysis shows that the use of a multiprocessor system enhances the system performance by about 87%. In addition, the proposed design is scalable, which is necaccery in this application where the number of features changes repeatedly.

• 디지털융복합연구
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• 제10권11호
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• pp.331-335
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• 2012

핸드폰에 사용되는 카메라의 발달로 자동초점용 렌즈에 대한 많은 연구가 진행되어 왔다. 다양한 종류의 자동초점용 액추에이터 중에서 VCM(Voice Coil Motor)이 가장 많이 사용되고 있다. 이 VCM은 자석, 코일, 요크 등의 모양에 따라서 구성되는 자계의 흐름을 달리하여 원하는 수준의 자동초점 조절이 가능한 핸드폰용 카메라가 만들어지고 있다. 본 연구에서는 유한요소 해석프로그램인 ANSYS$^{TM}$를 이용하여 산업체에서 사용되는 다양한 구조의 렌즈 중 가장 경제적인 모델을 선택하여 전자기 분석을 수행하였다. 이 전자기 해석을 통하여 효율적인 렌즈 모듈 설계 방법을 제시한다.

• 마이크로전자및패키징학회지
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• 제27권2호
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• pp.1-10
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• 2020

The technology and market size of image sensors continue to develop thanks to the release of image sensors that exceed 100 million pixels in 2019 and expansion of black box camera markets for vehicles in addition to existing mobile applications. We review the technology flow of image sensors that have been constantly evolving for 40 years since Hitachi launched a 200,000-pixel image sensor in 1979. Although CCD has made inroads into image sensor market for a while based on good picture quality, CMOS image sensor (CIS) with active pixels has made inroads into the market as semiconductor technology continues to develop, since the electrons generated by the incident light are converted to the electric signals in the pixel, and the power consumption is low. CIS image sensors with superior characteristics such as high resolution, high sensitivity, low power consumption, low noise and vivid color continue to be released as the new technologies are incorporated. At present, new types of structures such as Backside Illumination and Isolation Cell have been adopted, with better sensitivity and high S/N ratio. In the future, new photoconductive materials are expected to be adopted as a light absorption part in place of the pn junction.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.