• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.777-784
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• 2009

Recently, the importance of geoCRM (geographic Customer Relationship Management) systems are growing rapidly. So, result of the recognition that their applications extend well beyond the traditional CRM systems with the advent of ubiquitous environment and generalized location based services. A majority of traditional CRM systems are either incapable of managing spatial data or are not user-friendly when doing so. On the other hand, the geoCRM systems can be built as providing the geographic-based functions about CRM, including spatial and market analyses and the visualization of customer data, etc. However, it lacks the specific model and implementation of the geoCRM systems, being caused by the incomprehension of needs, the absence of related standards and the difficulties of development, and so on. In this paper, we develop a new spatial analysis supporting system that to enhance productivity through the convenient use and management of spatial data. The functionality provided by our system includes a set of analysis functions based on data mining techniques which allow a user to affect powerful transformation on spatial data. Particularly, both spatial data and non-spatial attributes can be efficiently handled as an object through our OODBMS.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.188-194
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• 2004

With a remarkable advance in CMOS (complimentary metal-oxide-semiconductor) process technology, a variety of vision sensors with signal processing circuits for complicated functions are actively being developed. Especially, as the principles of signal processing in human retina have been revealed, a series of vision chips imitating human retina have been reported. Human retina is able to detect the edge and motion of an object effectively. The edge detection among the several functions of the retina is accomplished by the cells called photoreceptor, horizontal cell and bipolar cell. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge and motion detection. The designed vision chip was fabricated using $0.6{\mu}m$ CMOS process and the characteristics were measured. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.933-934
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• 2006

High level perceptual tasks such as context understanding, SLAM and object recognition are essential for intelligent robot to provide services for human supports. Those intelligent robots often use camera sensor for vision information, sonar or laser sensor for range information, encoder for angular velocity of wheel and so on. The information is generated at different time intervals by the different H/W devices and S/W algorithms. The generation of high level information requires the specific mixture of low level information. And the information should be represented to be useful for robots to use in their ecological niche. In conventional robot systems, perceptual module requires the resource to use by tightly coupling whenever it is needed. So the resource and information cannot be easily shared and even could be invalid for the delayed information. In this paper, we propose a synchronization system of robot-centered information for context understanding. Our system represents information for the robot capacity and synchronizes the information that is asynchronously generated, where is employed the black-board architecture.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.73-80
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• 2018

This study introduces an interactive drawing system, a tool that allows user to sketch and draw with his own intentions. The proposed system enables the user to express more creatively through a tool that allows the user to reproduce his original idea as a drawing and transform it using his body. The user can actively participate in the production of the artwork by studying the unique formative language of the spectator. In addition, the user is given an opportunity to experience a creative process by transforming arbitrary drawing into various shapes according to his gestures. Interactive drawing systems use the segmentation of the drawing image as a way to extend the user's initial drawing idea. The system includes transforming a two-dimensional drawing into a volume-like form such as a three-dimensional drawing using image segmentation. In this process, a psychological space is created that can stimulate the imagination of the user and project the object of desire. This process of drawing personification plays a role of giving the user familiarity with the artwork and indirectly expressing his her emotions to others. This means that the interactive drawing, which has changed to the emotional concept of interaction beyond the concept of information transfer, can create a cooperative sensation image between user's time and space and occupy an important position in multimedia society.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2471-2473
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• 2003

인간의 안구는 색과 모양을 식별하는 데에 관여하는 원추 세포와 물체의 명암을 구분하는 간상 세포로 구성되어지는 시세포를 가진다. 망막 위에 분포되어 있는 시세포들은 시축을 중심으로 각기 다른 밀도로 분포 되어 있다. 특히 광축과 만나는 중심 지역은 Fovea라고 하는 직경 1mm 정도의 작은 우물을 이루고 있는데 원추 세포들이 고해상도로 분포되어 있고 시신경과 일대일로 연결되어 있어 시각 처리의 중심이 된다. 특히, 글자나 물체를 인식하기 위해 인간은 대상물을 응시하여 대상물의 영상이 Fovca영역에 맺히도록 추적 운동을 계속한다. 본 논문에서는 인간의 눈과 유사한 망막 모델의 하나인 Log-polar Image를 이용한 물체 인식을 위해 물체를 Log-polar Image Plane의 중심에 위치시키기 위한 모멘텀(Momentum)기반 정합 알고리즘(Alignment Algorithm)을 제시한다. 이는 눈동자 운동이 가능한 능동형 시각 장치의 Tracking 및 Pursuit 동작 중에 밭생하는 추적 오차를 보상함으로써 운동 중에도 효과적인 물체 인식이 가능하게 한다. 또한, 물체를 Log-polar Image Plane의 중심에 위치시킴으로써 물체의 위치 이동, 회전이동 그리고 크기 변화에 무관하게 물체를 인식한 수 있음을 제시한다.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.267-273
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• 2021

Recently, the small-size mobile robots with remote-control are rapidly growth which market of mobile is increased in the world. Especially, the smart-phones are widely used for interface device in the small size of a mobile robot. The research goal is control system design which is applied to miniaturization of a mobile robot using smart-phone and it can be confirmed performance for designed system. Meanwhile, the fabrication of mini-mobile robot can also be remote-control operation through the WIFI performance of a smart-phone. The smart-phone is used to remote-control for robot operation which control data transmit to robot via the WIFI network. To drive the robot, we can observe by the smart-phone screen and it can easily adjust the robot drive condition and direction by smart-phone button. Consequentially, there was no malfunction and images were printed out well. However, in drive, because of blind spot, robot was bumped into obstacle. Therefore, the additional test is necessary to sensor for blind spot which sensor can be equipment to mobile robot. In addition, the experiment with robot object recognition is needed.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.175-177
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• 2021

The parking area for the disabled is a parking facility for the pedestrian disabled and is a parking space for securing pedestrian safety passage for the disabled. However, due to the lack of social awareness of areas for the disabled, the use of parking areas is restricted, and violations such as illegal parking and obstruction of parking are increasing every year. Therefore, in this study, we propose a system to crack down on illegal parking in handicapped parking areas using the YOLOv5 model, a deep learning object recognition model to improve parking interference within parking spaces.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.