• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.28-37
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• 2009

In this paper, we propose an obstacle localization method using a road feature based on a V-disparity map binarized by a maximum frequency value. In a conventional method, the detection performance is severely affected by the size, number and type of obstacles. It's especially difficult to extract a large obstacle or a continuous obstacle like a median strip. So we use a road feature as a new decision standard to localize obstacles irrespective of external environments. A road feature is proper to be a new decision standard because it keeps its rough feature very well in V-disparity under environments where many obstacles exist. And first of all, we create a binary V-disparity map using a maximum frequency value to extract a road feature easily. And then we compare the binary V-disparity map with a median value to remove noises. Finally, we use a linear interpolation for rows which have no value. Comparing this road feature with each column value in disparity map, we can localize obstacles robustly. We also propose a post-processing technique to remove noises made in obstacle localization stage. The results in real road tests show that the proposed algorithm has a better performance than a conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.855-870
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• 2020

Windows are key components of building facades. Detecting windows, crucial to 3D semantic reconstruction and scene parsing, is a challenging task in computer vision. Early methods try to solve window detection by using hand-crafted features and traditional classifiers. However, these methods are unable to handle the diversity of window instances in real scenes and suffer from heavy computational costs. Recently, convolutional neural networks based object detection algorithms attract much attention due to their good performances. Unfortunately, directly training them for challenging window detection cannot achieve satisfying results. In this paper, we propose an approach for window detection. It involves an improved Faster R-CNN architecture for window detection, featuring in a window region proposal network, an RoI feature fusion and a context enhancement module. Besides, a post optimization process is designed by the regular distribution of windows to refine detection results obtained by the improved deep architecture. Furthermore, we present a newly collected dataset which is the largest one for window detection in real street scenes to date. Experimental results on both existing datasets and the new dataset show that the proposed method has outstanding performance.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.1-12
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• 2008

The expansion of media art has not only developed the digital technology but also given lots of environmental evolution to improve various fields of design as the main topic of the 21st century. The purpose of this study is aimed at proposing the new design that integrates fashion accessaries with media art technology. This will be done by understanding the social environment in digital ages and studying technology of design based on a variety of literature about changes in our society, neo value, vision, culture and art with fundamental notion of media art. First stage for this study, put an idea into just fashion accessary design because it is not sufficient to incoporate fashion and media art technology. The presented OLED(Organic Light Emitting Diodes) in this study is a kind of display to be in a limelight in the next generation and can be applied to various field of design. media art simultaneously moved into the scope of artistic debates. As a result, we can found that the use of audiovisual introduced numerous new aspects to the conceptual and aesthetic engagement with questions of conception. Today, the presented forms of art and inter-action from the closed -circuit work to interactive media art installations to open process-exist as parallel possibilities.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.520-524
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• 2009

In compressed color images, colors are usually represented by luminance and chrominance (YCbCr) components. Considering characteristics of human vision system, chrominance (CbCr) components are generally represented more coarsely than luminance component. Aiming at possible recovery of chrominance components, we propose a model-based chrominance estimation algorithm where color images are modeled by a Markov random field (MRF). A simple MRF model is here used whose local conditional probability density function (pdf) for a color vector of a pixel is a Gaussian pdf depending on color vectors of its neighboring pixels. Chrominance components of a pixel are estimated by maximizing the conditional pdf given its luminance component and its neighboring color vectors. Experimental results show that the proposed chrominance estimation algorithm is effective for quality improvement of compressed color images such as JPEG and JPEG2000.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.05a
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• pp.15.2-15.2
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• 2009

Manufacturing of printed electronics using printing technology has begun to get into the hot issue in many ways due to the low cost effectiveness to existing semi-conductor process. This technology with both low cost and high productivity, can be applied in the production of organic thin film transistor (OTFT), solar cell, radio frequency identification (RFID) tag, printed battery, E-paper, touch screen panel, black matrix for liquid crystal display (LCD), flexible display, and so forth. The emerging technology to manufacture the products in mass production is roll-to-roll printing technology which is a manufacturing method by printings of multi-layered patterns composed of semi-conductive, dielectric and conductive layers. In contrary to the conventional printing machines in which printing precision is about $50~100{\mu}m$, the printing machines for printed electronics should have a precision under $30{\mu}m$. In general, in order to implement printed electronics, narrow width and gap printing, register of multi-layer printing by several printing units, and printing accuracy of under $30{\mu}m$ are all required. We developed the roll-to-roll printing equipment used for printed electronics, which is composed of un-winder, re-winder, tension measurement system, feeding units, dancer systems, guide unit, printing unit, vision system, dryer units, and various auxiliary devices. The equipment is designed based on cantilever type in which all rollers except printing ones have cantilever types, which could give more accurate machine precision as well as convenience for changing rollers and observing the process.

• Smart Structures and Systems
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• v.24 no.5
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• pp.587-595
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• 2019

Deformation measurement of large scale structures, such as the ground beds of high-rise buildings, tunnels, bridge, and railways, are important for insuring service quality and safety. The pose-relay videometrics method and displacement-relay videometrics method have already presented to measure the pose of non-intervisible objects and vertical subsidence of unstable areas, respectively. Both methods combine the cameras and cooperative markers to form the camera series networks. Based on these two networks, we propose two novel videometrics methods with closed-loop camera series network for deformation measurement of large scale structures. The closed-loop camera series network offers "closed-loop constraints" for the camera series network: the deformation of the reference points observed by different measurement stations is identical. The closed-loop constraints improve the measurement accuracy using camera series network. Furthermore, multiple closed-loops and the flexible combination of camera series network are introduced to facilitate more complex deformation measurement tasks. Simulated results show that the closed-loop constraints can enhance the measurement accuracy of camera series network effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.333-334
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• 2016

Recently, with the development of technology for the virtual reality services, the virtual reality technology has been to use various application services. However, because it is difficult to secure a non-Augmented Reality Virtual Reality in this case it has a vision problem that can be fixed in a service only, not removable. In this paper, we propose a technique of application iBeacon signal by applying the technology of the indoor location-based service using a virtual reality system described in iBeacon ensure the mobility in a virtual space, and can detect the collisions with other moving objects.

• Corrosion Science and Technology
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• v.18 no.6
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• pp.253-257
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• 2019

A deep learning based real-time painting surface inspection algorithm is proposed herein, designed for developing an autonomous inspection drone. The painting surface inspection is usually conducted manually. However, the manual inspection has a limitation in obtaining accurate data for correct judgement on the surface because of human error and deviation of individual inspection experiences. The best method to replace manual surface inspection is the vision-based inspection method with a camera, using various image processing algorithms. Nevertheless, the visual inspection is difficult to apply to surface inspection due to diverse appearances of material, hue, and lightning effects. To overcome technical limitations, a deep learning-based pattern recognition algorithm is proposed, which is specialized for painting surface inspections. The proposed algorithm functions in real time on the embedded board mounted on an autonomous inspection drone. The inspection results data are stored in the database and used for training the deep learning algorithm to improve performance. The various experiments for pre-inspection of painting processes are performed to verify real-time performance of the proposed deep learning algorithm.

• Korean Journal of Computational Design and Engineering
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• v.16 no.1
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• pp.1-10
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• 2011

In this paper, we propose an AR-based tangible interaction using a finger fixture for virtual evaluation of digital handheld products. To realize tangible interaction between a user and a product in a computer-vision based AR environment, we uses two types of tangible objects: a product-type object and a finger fixture. The product-type object is used to acquire the position and orientation of the product, and the finger fixture is used to recognize the position of a finger tip. The two objects are fabricated by RP technology and AR markers are attached to them. The finger fixture is designed to satisfy various requirements with an ultimate goal that the user holding the finger fixture in his or her index finger can create HMI events by touching specified regions (buttons or sliders) of the product-type object with the finger tip. By assessing the accuracy of the proposed interaction, we have found that it can be applied to a wide variety of digital handheld products whose button size is not less than 6 mm. After performing the design evaluation of several handheld products using the proposed AR-based tangible interaction, we received highly encouraging feedback from users since the proposed interaction is intuitive and tangible enough to provide a feeling like manipulating products with human hands.