• Journal of Biosystems Engineering
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• v.37 no.1
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• pp.65-74
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• 2012

Purpose: An autonomous robot was developed for harvesting strawberries cultivated in bench-type systems. Methods: The harvest robot consisted of four main components: an autonomous vehicle, a manipulator with four degrees of freedom (DOF), an end effector with two DOFs, and a color computer vision system. Strawberry detection was performed based on 3D image and distance information obtained from a stereo CCD color camera and a laser device, respectively. Results: In this work, a Cartesian type manipulator system was designed, including an intermediate revolute axis and a double driven arm-based joint axis, so that it could generate collision-free motions during harvesting. A DC servomotor-driven end-effector, consisting of a gripper and a cutter, was designed for gripping and cutting the strawberry stem without damaging the strawberry itself. Real-time position tracking algorithms were developed to detect, recognize, trace, and approach strawberries under natural light conditions. Conclusion: The developed robot system could harvest a strawberry within 7 seconds without damage.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.359-366
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• 2015

TMJ(TemporoMandibular Joint) is considered as the most important articulation in human body for maintaining the balance. Thus it is one of the main treatment areas in Chiropractic. Instead of Chiropractic treatment, NOSICK, a TMJ balancing device, can be used. As there is no such device to quantify the effect of NOSICK, a system was developed to measure the effect of NOSICK. This system is composed of stereo vision, infrared lights, and infrared through filter, etc. It requires optical markers for the measurement. 8 land markers were selected from the face which will show different displacement as NOSICK is applied. 11 test subjects were measured with the system developed with and without NOSICK applied. Quantifiable displacement of markers before and after applying NOSICK was successfully measured with the system developed.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.38-46
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• 2010

In this paper, an autonomous surveillance-tracking system for Workers monitoring basing on the stereo vision scheme is proposed. That is, analysing the characteristics of the cross-axis camera system through some experiments, a optimized stereo vision system is constructed and using this system an intelligent worker surveillance-tracking system is implemented, in which a target worker moving through the environments can be detected and tracked, and its resultant stereo location coordinates and moving trajectory in the world space also can be extracted. From some experiments on moving target surveillance-tracking, it is analyzed that the target's center location after being tracked is kept to be very low error ratio of 1.82%, 1.11% on average in the horizontal and vertical directions, respectively. And, the error ratio between the calculation and measurement values of the 3D location coordinates of the target person is found to be very low value of 2.5% for the test scenario on average. Accordingly, in this paper, a possibility of practical implementation of the intelligent stereo surveillance system for real-time tracking of a target worker moving through the environments and robust detection of the target's 3D location coordinates and moving trajectory in the real world is finally suggested.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.12a
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• pp.597-604
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• 1999

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.519-524
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• 2009

This paper describes a new sensor system for 3D environment perception using stereo structured infrared light sources and a camera. Environment and obstacle sensing is the key issue for mobile robot localization and navigation. Laser scanners and infrared scanners cover $180^{\circ}$ and are accurate but too expensive. Those sensors use rotating light beams so that the range measurements are constrained on a plane. 3D measurements are much more useful in many ways for obstacle detection, map building and localization. Stereo vision is very common way of getting the depth information of 3D environment. However, it requires that the correspondence should be clearly identified and it also heavily depends on the light condition of the environment. Instead of using stereo camera, monocular camera and two projected infrared light sources are used in order to reduce the effects of the ambient light while getting 3D depth map. Modeling of the projected light pattern enabled precise estimation of the range. Two successive captures of the image with left and right infrared light projection provide several benefits, which include wider area of depth measurement, higher spatial resolution and the visibility perception.

• Korean Journal of Cognitive Science
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• v.14 no.1
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• pp.17-28
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• 2003

In order to provide natural images with a specified depth through three-dimensional display system, the stereo images should be similar to those projected from real environment as much as possible. Even when two persons see an identical scene, the binocular Parallax between two images of an object varies as a function of one's inter-pupilary distance (IPD). In this study, we investigated whether individual differences, such as IPD and accommodative vergence, would affect the perception of three dimensional scene provided by stereo-images. Results showed that a person's IPD is correlated with the limit of screen and binocular parallax for single vision, and affects the perceived depth of an object on fixation. More specifically, with longer IPD the limit of screen and binocular parallax for single vision is decreased, and the perceived depth is reduced. These results suggest that the screen and binocular parallax of an object should be calibrated with regard to users IPD to provide natural stereo-images with a specified depth and to Prevent double vision.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.25-33
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• 2009

In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.9
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• pp.639-646
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• 2022

Landing site searching algorithms are developed for a quadrotor using a depth map in unknown environment. Guidance and control system of Unmanned Aerial Vehicle (UAV) consists of a trajectory planner, a position and an attitude controller. Landing site is selected based on the information of the depth map which is acquired by a stereo vision sensor attached on the gimbal system pointing downwards. Flatness information is obtained by the maximum depth difference of a predefined depth map region, and the distance from the UAV is also considered. This study proposes three landing methods and compares their performance using various indices such as UAV travel distance, map accuracy, obstacle response time etc.

• Journal of Sensor Science and Technology
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• v.7 no.2
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• pp.124-130
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• 1998

High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three computational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a $64{\times}32$ bit instruction cache and two $1024{\times}32$ bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With $512{\times}512$ pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.318-324
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• 2017

We introduced a stereo camera on the aircraft to detect flight objects and to estimate the 3D position of them. The Saliency map algorithm based on PCT was proposed to detect a small object between clouds, and then we processed a stereo matching algorithm to find out the disparity between the left and right camera. In order to extract accurate disparity, cost aggregation region was used as a variable region to adapt to detection object. In this paper, we use the detection result as the cost aggregation region. In order to extract more precise disparity, sub-pixel interpolation is used to extract float type-disparity at sub-pixel level. We also proposed a method to estimate the spatial position of an object by using camera parameters. It is expected that it can be applied to image - based object detection and collision avoidance system of autonomous aircraft in the future.