• ETRI Journal
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• v.28 no.2
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• pp.216-218
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• 2006

This letter presents the design for a low-profile planar inverted-F antenna (PIFA) that can be stuck to metallic objects to create a passive radio frequency identification (RFID) tag in the UHF band. The designed PIFA, which uses a dielectric substrate for the antenna, consists of a U-slot patch for size reduction, several shorting pins, and a coplanar waveguide feeding structure to easily integrate with an RFID chip. The impedance bandwidth and maximum gain of the tag antenna are about 0.3% at 914 MHz for a voltage standing wave ratio (VSWR) of less than 2 and 3.6 dBi, respectively. The maximum read range is about 4.5 m as long as the tag antenna is on a metallic object.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.386-393
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• 2012

In this paper, we propose an efficient multi-object recognition and tracking scheme based on interest points of objects and their feature descriptors. To do that, we first define a set of object types of interest and collect their sample images. For sample images, we detect interest points and construct their feature descriptors using SURF. Next, we perform a statistical analysis of the local features to select representative points among them. Intuitively, the representative points of an object are the interest points that best characterize the object. in addition, we make the movement vectors of the interest points based on matching between their SURF descriptors and track the object using these vectors. Since our scheme treats all the objects independently, it can recognize and track multiple objects simultaneously. Through the experiments, we show that our proposed scheme can achieve reasonable performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2961-2967
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• 2014

Nowadays, a private protection act has come into effect which demands for the protection of personal image information obtained by the CCTV. According to this act, the object out of interest has to be mosaicked such that it can not be identified before the image is sent to the investigation office. Meanwhile, the demand for digital videos obtained by CCTV is also increasing for digital forensic. Therefore, due to the two conflicting demands, the demand for a solution which can automatically mask an object in the CCTV video is increasing and related IT industry is expected to grow. The core technology in developing a target masking solution is the object tracking technique. In this paper, we propose an object tracking technique which suits for the application of CCTV video object masking as a postprocess. The proposed method simultaneously uses the motion and the color information to produce a stable tracking result. Furthermore, the proposed method is based on the centroid shifting method, which is a fast color based tracking method, and thus the overall tracking becomes fast.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.153-161
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• 2019

Discrimination of media object segments in wireless home proxies has a significant impact on caching delay, and caching delay degrades the performance of the proxy. In this paper, we propose a Single Fetching Smart Caching (SFSC) strategy and a Multi-Fetching Smart Caching (MFSC) strategy to improve the proxy performance of the home network and improve the caching performance for media object segments. The SFSC strategy is a technique that performs caching by sequential fetching of object segments requested by the home node one at a time, which guarantees a faster cache hit rate, and the MFSC strategy is a technique that caches the media object segments by blocking object segments requested by the home node one at a time, which improves the throughput of cache. Simulation results show that the cache hit rate and the caching delay are more efficient than the MFSC technique, and the throughput of the object segment is more efficient than that of the SFSC technique.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.273-277
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• 2005

In this paper, we study on adaptation of the kalman filter for FDS(fishery detection system) to protect and aquaculture farms. The FDS will detect a robbing vessel with real time and a variance of the position of fishing fields. The kalman filter for tracking system that can be detect and track the approaching object without mounting F-AIS(Fishery Automatic Identification System) is applied. Some simulation results for the acceleration object with white noise is showed and the possibility of adaptation for tracking system is discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3668-3674
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• 2009

Use case diagram is used for defining inter-action between users and systems in object-oriented modeling. It is very important to defining users' requirements for efficient software development. In this paper, we propose a object-oriented modeling process using hierarchical use case analysis for designing class model. First, We define many use case diagrams by several hierarchical modeling level. And next, we can also design class model using the use case diagrams. Our proposed modeling process provides interaction between use case model and class model. That can make us to check the modeling process during the software development. Using the proposed object-oriented modeling we can develop software based on users' requirements. It is very useful for class modeling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2057-2064
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• 2010

With the development of wireless network technology, the location information of a spatiotemporal object which changes their location is used in various application. Each spatiotemporal object has many location information, hence it is inefficient to search all trajectory information of spatiotemporal objects for a range query. In this paper, we propose an efficient method which divides a trajectory and stores its division data on restricted storage space. Using suboptimal split algorithm, an extended split algorithm that minimizes the volume of EMBRs(Extended Minimum Bounding Box) is designed and simulated. Our experimental evaluation confirms the effectiveness and efficiency of our proposed splitting policy

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.96-100
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• 2010

In this paper we present a position tracking system that checks the locations of moving targets in real-time. The system confirms that unknown object invades in watch area using 2 infrared sensors and detect the distance from each sensor to object using 4 ultrasonic sensors, and calculate the position of moving object in x-y coordinate. We specially present an algorithm that decide the location of target in case of target is detected in 2 sensors because of radiation beam width of ultrasonic sensor. We established the algorithm to hardware system and tested the system within a laboratory, and confirmed that the designed system tracked an object exactly in real-time.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.97-104
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• 2023

This paper is related to object segmentation using ESRGAN(Enhanced Super Resolution GAN) and SSS(Semantic Soft Segmentation). The segmentation performance of the object segmentation method using Mask R-CNN and SSS proposed by the research team in this paper is generally good, but the segmentation performance is poor when the size of the objects is relatively small. This paper is to solve these problems. The proposed method aims to improve segmentation performance of small objects by performing super-resolution through ESRGAN and then performing SSS when the size of an object detected through Mask R-CNN is below a certain threshold. According to the proposed method, it was confirmed that the segmentation characteristics of small-sized objects can be improved more effectively than the previous method.

• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1254-1269
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• 2023

This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction. A large amount of data is required to train CNNs effectively. Still, since UAVs capture only a limited number of images, we propose a data augmentation method that can effectively increase data. And most occupancy prediction predicts occupancy by designing a CNN-based object detector for an image and counting the number of recognized objects or calculating the number of pixels occupied by an object. These methods require complex occupancy rate calculations; the accuracy depends on whether the object features of interest are visible in the image. However, in this study, CNN is not approached as a corn object detection and classification problem but as a function approximation and regression problem so that the occupancy rate of corn objects in an image can be represented as the CNN output. The proposed method effectively estimates occupancy for a limited number of cornfield photos, shows excellent prediction accuracy, and confirms the potential and scalability of deep learning.