• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.10a
• /
• pp.592-595
• /
• 2001

원거리에서 무접촉 거리 계측(ranging)은 군용 장비나 건설, 항해, 자동화 등에 매우 중요하다. 계측방식은 active와 passive 방식으로 구분되는데, active방식은 laser나 microwave, 초음파 등의 time of flight를 이용하거나 레이저 조사(illumination)에 대한 카메라 영상을 해석하는 등의 다양한 방식이 있으나 장치가 복잡하고, passive 방식은 stereo camera의 양안 영상을 이용하거나 focus 특성을 이용하는 방식 등이 있으나 대부분 연산 시간이 많이 요구된다. 본 연구에서는 수동식 스테레오 카메라에서 양안시차를 추출하여 triangulation으로 목표점(target point)의 거리를 측정하는 것을 기본 방식으로 하여, 기존 거리 산출 방식에서 연산 시간이 많이 소요되는 연산 과정을 효율적이고 고속으로 수행할 수 있도록 새로운 방식을 제안하였다. 즉, 목표점에서의 양안 edge 영상을 구하며, 이 영상의 accumulation profile을 correlation하여, 거리 연산의 핵심 요소인 양안 시차를 고속으로 추출하는 알고리즘을 제안하였다. 또한, 제안 방식의 효율성을 실험 결과를 통하여 보였다.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.369-371
• /
• 2009

휴머노이드 로봇에서 스스로 환경을 인식하는 기술은 필수적으로 필요하다. 그러나 정확하게 환경을 인식하기 위해서는 휴머노이드 움직임을 추정하여 보정해야 한다. 따라서 본 논문에서는 type-2 퍼지셋을 이용하여 휴머노이드 로봇의 움직임을 스테레오 비전기반으로 추정하는 방법을 제안하고자 한다. 본 연구에서는 우선 스테레오 비전으로 얻은 Disparity Map을 Type-2 퍼지셋을 이용하여 추적할 대상을 추출한다. 추출된 대상은 보다 정확한 계산을 위하여 Wavelet Transform을 이용하여 정보량을 확장하였으며, 그 결과로 얻어진 결과영상들은 다시 Least suqare approximation과 Type-2 퍼지셋을 이용하여 하나의 결과값으로 나타내어진다. 연속된 두 이미지의 움직임을 추정함으로써 로봇의 움직임을 추정하게 된다. 제안된 방법은 실험을 통하여 그 추정 정확도나 연산속도 면에서 효율적임을 알 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.1
• /
• pp.60-65
• /
• 2010

This paper describes the results of 2D mapping, feature detection and matching to create the surrounding environment in the mounted stereo camera on Mobile robot. Extract method of image's feature in real-time processing for quick operation uses the edge detection and Sum of Absolute Difference(SAD), stereo matching technique can be obtained through the correlation coefficient. To estimate the location of a mobile robot using ZigBee beacon and encoders mounted on the robot is estimated by Kalman filter. In addition, the merged gyro scope to measure compass is possible to generate map during mobile robot is moving. The Simultaneous Localization and Mapping (SLAM) of mobile robot technology with an intelligent robot can be applied efficiently in human life would be based.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.11
• /
• pp.2388-2396
• /
• 2012

This paper is on an simplified orthogonal projection method which cancel the acoustic echo signals in the stereo acoustic echo canceller. Comparing with the NLMS algorithm which is widely used for simplicity and stability, it shows that this method has the improvement of the convergence performances for signals with the high auto-correlation, and has small computational quantities. To verify the convergence characteristics of the proposed algorithm, we simulated about various input signals. And we compared the results of simulation for this algorithm with the ones for the NLMS algorithm. By these works, it was proved that the stereo acoustic echo canceller adopting the proposed algorithm shows about 3dB more high ERLE than the NLMS algorithm for the white noise signals, and 5dB for the colored voice signals.

• Journal of Korea Multimedia Society
• /
• v.15 no.6
• /
• pp.711-721
• /
• 2012

The objective of this study is to propose an efficient 3D reconstruction method for developing a stereo-vision-based haptics system which can replace "robotic eyes" and "robotic touch." The haptic rendering for 3D images requires to capture depth information and edge information of stereo images. This paper proposes the 3D reconstruction methods using LoG(Laplacian of Gaussian) algorithm and DoG(Difference of Gaussian) algorithm for edge detection in addition to the basic 3D depth extraction method for better haptic rendering. Also, some experiments are performed for evaluating the CPU time and the error rates of those methods. The experimental results lead us to conclude that the DoG method is more efficient for haptic rendering. This paper may contribute to investigate the effective methods for 3D image reconstruction such as in improving the performance of mobile patrol robots.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.3
• /
• pp.21-29
• /
• 2011

This paper presents a method that estimates distance and velocity of an object with reliability regardless of maneuver status of the target in stereo vision system. A stereo vision system can calculate a distance with disparity from left and right images. However, the distance estimation error may occur due to quantization error of image pixel. A sub-pixel interpolation method minimizes the quantization error and estimates accurate disparity with real value. Extended Kalman filter (EKF) was used to minimize the error covariance and estimate the object's velocity. However, divergence problem occurs due to model uncertainty when a target maneuvers highly, which makes the estimation error increase. In this paper, we propose a virtual model extended Kalman filter (VMEKF) method that minimizes the processing time and provides reliable estimation ability regardless of maneuver status. Computer simulations and experimental results in real road environments demonstrate that the proposed method gives a reliable estimation performance and reduces processing time under various maneuver status while comparing other estimation filters.

• The KIPS Transactions:PartB
• /
• v.10B no.2
• /
• pp.135-142
• /
• 2003

Robust extraction of 3D object's features, shape and global motion information from 2D image sequence is described. The object's 21 feature points on the pyramid type synthetic object are extracted automatically using color transform technique. The extracted features are used to recover the 3D shape and global motion of the object using stereo paraperspective camera model and sequential SVD(Singuiar Value Decomposition) factorization method. An inherent error of depth recovery due to the paraperspective camera model was removed by using the stereo image analysis. A 30 synthetic object with 21 features reflecting various position was designed and tested to show the performance of proposed algorithm by comparing the recovered shape and motion data with the measured values.

• Journal of KIISE:Software and Applications
• /
• v.28 no.7
• /
• pp.501-510
• /
• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.2
• /
• pp.198-204
• /
• 2012

Tracking and recognition of robots are required for the cooperation task of robots in various environments. In the paper, a tracking control system of moving robot using stereo image processing, code-book model and fuzzy controller is proposed. First, foreground and background images are separated by using code-book model method. A candidate region is selected based on the color information in the separated foreground image and real distance of the robot is estimated from matching process of depth image that is acquired through stereo image processing. The open and close processing of image are applied and labeling according to the size of mobile robot is used to recognize the moving robot effectively. A fuzzy tracking controller using distance information and mobile information by stereo image processing is designed for effective tracking according to the movement velocity of the target robot. The proposed fuzzy tracking control method is verified through tracking experiments of mobile robots with stereo camera.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.1
• /
• pp.55-61
• /
• 2008

A real-time three-dimensional vision is a passive system, which would support various applications including collision avoidance, home networks. It is a good alternative of active systems, which are subject to interference in noisy environments. In this paper, we designed a SAD correlator with respect to resource usage for a real-time three-dimensional vision system. Regular structures, linear data flow and abundant parallelism make the correlation algorithm a good candidate for a reconfigurable hardware. We implemented two versions of SAD correlator in HDL and synthesized them to determine resource requirements and performance. From the experiment we show that the SAD correlator fits into reconfigurable hardware in marginal cost and can handle about 30 frames/sec with $640{\times}480$ images.