• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.363-370
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• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

• Journal of IKEEE
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• v.24 no.2
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• pp.502-506
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• 2020

With the development of autonomous driving technology, the importance of object recognition technology is increasing. Haze removal is required because the hazy weather reduces visibility and detectability in object recognition. However, the image from which the haze has been removed cannot properly reflect the unique color, and a detection error occurs. In this paper, we use CIE1931 color coordinate system to extend or reduce the color area to provide algorithms and hardware that reflect the colors of the real world. In addition, we will implement hardware capable of real-time processing in a 4K environment as the image media develops. This hardware was written in Verilog and implemented on the SoC verification board.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.496-500
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• 1998

Not merely running at the designated constant speed as the classical cruise control, the adaptive cruise control (ACC) maintains safe headway distance when the front is blocked by other vehicles. One of the most essential part of ACC System is the range sensor which can measure the position and speed of all objects in front continuously, ignore all irrelevant objects, distinguish vehicles in different lanes and lock on to the closest vehicle in the same lane. In this paper, the hierarchical object recognition algorithm (HORA) is proposed to process raw scanning laser data and acquire valid distance to target vehicle. HORA contains two principal concepts. First, the concept of life quantifies the reliability of range data to filter off the spurious detection and preserve the missing target position. Second, the concept of conformation checks the mobility of each obstacle and tracks the position shift. To estimate and predict the vehicle position Kalman filter is used. Repeatedly updated covariance matrix determines the bound of valid data. The algorithm is emulated on computer and tested on-line with our ACC vehicle.

• Journal of IKEEE
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• v.22 no.4
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• pp.1180-1187
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• 2018

This paper had implemented the underwater stage through interaction with fish robots and visitors in the background of traditional fairy tales using 3D floating hologram in an aquarium. The recognition of the object position of the spectator and the underwater robot were performed using the color recognition algorithm. Also, the position tracking algorithm was proposed to follow the object of the visitor and the original fairy tale. This experimental system consists of fish robot, camera, KIOSK for underwater robot control and beam project for underwater imaging. This experiment was carried out by the National Busan Science Museum, and it had satisfied the performance of the underwater stage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.358-365
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• 2017

In this paper, we propose an object recognition method using image information to improve the efficiency of visual servoingfor industrial manipulators in industry. This is an image-processing method for real-time responses to an abnormal situation or to external environment change in a work object by utilizing camera-image information of an industrial manipulator. The object recognition method proposed in this paper uses the Otsu method, a thresholding technique based on separation of the V channel containing color information and the S channel, in which it is easy to separate the background from the HSV channel in order to improve the recognition rate of the existing Harris Corner algorithm. Through this study, when the work object is not placed in the correct position due to external factors or from being twisted,the position is calculated and provided to the industrial manipulator.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.342-347
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• 2008

Face tracking and recognition are difficult problems because the face is a non-rigid object. If the system tries to track or recognize the unknown face continuously, it can be more hard problems. In this paper, we propose the method to track and to recognize the face of the unknown person on video sequences using linear combination of nonlinear manifold models that is constructed in the system. The arbitrary input face has different similarities with different persons in system according to its shape or pose. Do we can approximate the new nonlinear manifold model for the input face by estimating the similarities with other faces statistically. The approximated model is updated at each frame for the input face. Our experimental results show that the proposed method is efficient to track and recognize for the arbitrary person.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Archives of design research
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• v.17 no.2
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• pp.269-278
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• 2004

This research categorizes various icons that used in PDAs according to symbolization patterns, operating systems and support for color display. Since different icons vary in communication capacity I executed this research to verify it positively. In result, PDA loons were found to have different intuitive communication capacity according to its functions, symbolization pattern, operating system and use of color. \circled1 Icons which have similar object as ones that are used on desktop computer and icons with accurate, simple expression seems to have higher intuitive communication capacity among the icons categorized by functions. \circled2 Among the icons categorized by symbolization pattern, ones that express the action related to their functions have the highest recognition accuracy and longer delay before recognition. \circled3 Among the icons categorized by operating systems, ones that have concrete expression of object and a number of representation elements have higher recognition accuracy and longer delay before recognition. \circled4 Among the icons categorized by color and grayscale, ones with color have superior communication capacity due to additional stimulation although LCDs in most PDAs have limited color depth.

• Toxicological Research
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• v.31 no.1
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• pp.17-23
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• 2015

Excessive manganese (Mn) in the brain promotes a variety of abnormal behaviors, including memory deficits, decreased motor skills and psychotic behavior resembling Parkinson's disease. Hereditary hemochromatosis (HH) is a prevalent genetic iron overload disorder worldwide. Dysfunction in HFE gene is the major cause of HH. Our previous study has demonstrated that olfactory Mn uptake is altered by HFE deficiency, suggesting that loss of HFE function could alter manganese-associated neurotoxicity. To test this hypothesis, Hfe-knockout ($Hfe^{-/-}$) and wild-type ($Hfe^{+/+}$) mice were intranasally-instilled with manganese chloride ($MnCl_2$ 5 mg/kg) or water daily for 3 weeks and examined for memory function. Olfactory Mn diminished both short-term recognition and spatial memory in $Hfe^{+/+}$ mice, as examined by novel object recognition task and Barnes maze test, respectively. Interestingly, $Hfe^{-/-}$ mice did not show impaired recognition memory caused by Mn exposure, suggesting a potential protective effect of Hfe deficiency against Mn-induced memory deficits. Since many of the neurotoxic effects of manganese are thought to result from increased oxidative stress, we quantified activities of anti-oxidant enzymes in the prefrontal cortex (PFC). Mn instillation decreased superoxide dismutase 1 (SOD1) activity in $Hfe^{+/+}$ mice, but not in $Hfe^{-/-}$ mice. In addition, Hfe deficiency up-regulated SOD1 and glutathione peroxidase activities. These results suggest a beneficial role of Hfe deficiency in attenuating Mn-induced oxidative stress in the PFC. Furthermore, Mn exposure reduced nicotinic acetylcholine receptor levels in the PFC, indicating that blunted acetylcholine signaling could contribute to impaired memory associated with intranasal manganese. Together, our model suggests that disrupted cholinergic system in the brain is involved in airborne Mn-induced memory deficits and loss of HFE function could in part prevent memory loss via a potential up-regulation of anti-oxidant enzymes in the PFC.