• JSTS:Journal of Semiconductor Technology and Science
• /
• v.16 no.1
• /
• pp.44-57
• /
• 2016

Rectification is used as a preprocessing to reduce the computation complexity of disparity estimation. However, rectification also requires a complex computation. To minimize the computing complexity, rectification using a lookup-table (R-LUT) has been introduced. However, since, the R-LUT consumes large amount of memory, rectification with compressed LUT (R-CLUT) has been introduced. However, the more we reduce the memory consumption, the more we need decoding overhead. Therefore, we need to attain an acceptable trade-off between the size of LUT and decoding overhead. In this paper, we present such a trade-off by adaptively combining simple coding methods, such as differential coding, modified run-length coding (MRLE), and Huffman coding. Differential coding is applied to transform coordinate data into a differential form in order to further improve the coding efficiency along with Huffman coding for better stability and MRLE for better performance. Our experimental results verified that our coding scheme yields high performance with maintaining robustness. Our method showed about ranging from 1 % to 16 % lower average inverse of compression ratio than the existing methods. Moreover, we maintained low latency with tolerable hardware overhead for real-time implementation.

• The Journal of the Korea Contents Association
• /
• v.11 no.1
• /
• pp.157-164
• /
• 2011

Since the movie "Avatar" made world-widely a big success, people's interest to 3D stereoscopic vision has been increasing explosively. However, it is hard to predict that for how long this tremendous attention to 3D stereoscopic would last; consumers have accumulated experience and predominant consciousness from social and cultural environmental various factors. This paper, we will try to see how people interact with 3D stereo through the empirical study. Using Jannett (2009)'s immersion questionnaire, we will measure how different people get immersed while playing game in 3D stereoscopic and 2D.

• Journal of Animal Environmental Science
• /
• v.8 no.3
• /
• pp.165-170
• /
• 2002

This study was carried out to measure the 3D-distance of a cow model teat for an application possibility on Robotic Milking System(RMS). A teat recognition algorithm was made to find 3D-distance of the model by using Gonzalrez's theory. Some of the results are as follows. 1 . In the distance measurement experiment on the test board, as the measured length, and the length between the center of image surface and the measured image point became longer, their error values increased. 2. The model teat was installed and measured the error value at the random position. The error value of X and Y coordinates was less than 5㎜, and that of Z coordinates was less than 20㎜. The error value increased as the distance of camera's increased. 3. The equation for distance information acquirement was satisfied with obtaining accurate distance that was necessary for a milking robot to trace teats, A teat recognition algorithm was recognized well four model cow teats. It's processing time was about 1 second. It appeared that a teat recognition algorithm could be used to determine the 3D-distance of the cow teat to develop a RMS.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.2
• /
• pp.69-79
• /
• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

• Journal of Digital Convergence
• /
• v.18 no.5
• /
• pp.425-432
• /
• 2020

Stereoscopic imaging is an important branch in the field of digital imaging, and has grown significantly over the last two decades through research and development. Hologram projection technology based on stereoscopic technology has been a social issue since the development of the Hungarian physicist Daniel Garber in 1947. It is becoming more and more important as stereoscopic works using similar technologies are applied to various fields. This study analyzed content cases using classical and creative stereoscopic technology from the perspective of digital image content design and explored the multiprotocol direction of holographic projection.

• Journal of Sensor Science and Technology
• /
• v.27 no.4
• /
• pp.216-220
• /
• 2018

In this paper, we present visual sensing techniques that can be used to teach a robot using a laser pointer. The light spot of an off-the-shelf laser pointer is detected and its movement is tracked on consecutive images of a camera. The three-dimensional position of the spot is calculated using stereo cameras. The light spot on the image is detected based on its color, brightness, and shape. The detection results in a binary image, and morphological processing steps are performed on the image to refine the detection. The movement of the laser spot is measured using two methods. The first is a simple method of specifying the region of interest (ROI) centered at the current location of the light spot and finding the spot within the ROI on the next image. It is assumed that the movement of the spot is not large on two consecutive images. The second method is using a Kalman filter, which has been widely employed in trajectory estimation problems. In our simulation study of various cases, Kalman filtering shows better results mostly. However, there is a problem of fitting the system model of the filter to the pattern of the spot movement.

• Journal of Computing Science and Engineering
• /
• v.11 no.3
• /
• pp.79-91
• /
• 2017

In this paper, the abdominal-deformation measurement scheme is conducted on a shape-flexible mannequin using the DIC technique in a stereo-vision system. Firstly, during the integer-pixel displacement search, a novel fractal dimension based on an adaptive-ellipse subset area is developed to track an integer pixel between the reference and deformed images. Secondly, at the subpixel registration, a new mutual-learning adaptive particle swarm optimization (MLADPSO) algorithm is employed to locate the subpixel precisely. Dynamic adjustments of the particle flight velocities that are according to the deformation extent of each interest point are utilized for enhancing the accuracy of the subpixel registration. A test is performed on the abdominal-deformation measurement of the shape-flexible mannequin. The experiment results indicate that under the guarantee of its measurement accuracy without the cause of any loss, the time-consumption of the proposed scheme is significantly more efficient than that of the conventional method, particularly in the case of a large number of interest points.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.555-560
• /
• 2008

두 장의 2차원 영상을 가지고 3차원을 재구성하기 위해서는 스테레오 정합을 이용한다. 이러한 이유로 그 동안에 많은 스테레오 정합에 대한 연구가 진행되었다. 스테레오 정합은 컴퓨터 기술의 발전과 더불어 좀 더 빠르고 높은 정확성을 보이고 있다. 하지만 속도와 정확성을 동시에 만족시키면서 대형영상에서도 동작할 수 있게 메모리을 적게 사용하는 방법은 많지가 않다. 본 논문에서는 이런 요구 조건을 만족시키기 위하여 새로운 스테레오 정합방법을 제시한다. 우리가 제시하는 새로운 방법은 다중 방향성 Greedy 알고리즘과 RANSAC을 반복적으로 사용하여 영상전체에 대한 스테레오 정합을 시도하는 방법이다. 우선 Greedy 알고리즘을 이용하여 여러 방향의 scan-line을 따라 깊이값 영상을 구한다. 그리고 이 여러 장의 깊이값 영상들의 분포를 RANSAC을 이용하여 신뢰영역을 찾아낸다. 구해진 신뢰영역을 바탕으로 Greedy 알고리즘과 RANSAC을 수 차례 반복하여 신뢰영역을 확장해 나가면 최종 깊이값 영상을 얻는다. 우리가 제안하는 알고리즘은 적은 메모리로도 큰 영상의 정합이 가능하고, 속도와 정확도 측면에서도 우수한 결과를 보인다.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.5
• /
• pp.406-410
• /
• 2005

A depth measurement system that consists of a single camera, a laser light source and a rotating mirror is investigated. The camera and the light source are fixed, facing the rotating mirror. The laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The camera detects the laser light location on object surfaces through the same mirror. The scan over the area to be measured is done by mirror rotation. Advantages are 1) the image of the light stripe remains sharp while that of the background becomes blurred because of the mirror rotation and 2) the only rotating part of this system is the mirror but the mirror angle is not involved in depth computation. This minimizes the imprecision caused by a possible inaccurate angle measurement. The detail arrangement and experimental results are reported.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.4
• /
• pp.517-524
• /
• 2007

This paper presents a global localization method using circular correlation of an omni-directional image. The localization of a mobile robot, especially in indoor conditions, is a key component in the development of useful service robots. Though stereo vision is widely used for localization, its performance is limited due to computational complexity and its narrow view angle. To compensate for these shortcomings, we utilize a single omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Nodes around a robot are extracted by the correlation coefficients of CHL (Circular Horizontal Line) between the landmark and the current captured image. After finding possible near nodes, the robot moves to the nearest node based on the correlation values and the positions of these nodes. To accelerate computation, correlation values are calculated based on Fast Fourier Transforms. Experimental results and performance in a real home environment have shown the feasibility of the method.