• Ocean Systems Engineering
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• v.10 no.4
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• pp.415-434
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• 2020

Detecting objects is important for the safe operation of ships, and enables collision avoidance, risk detection, and autonomous sailing. This study proposes a ship detection method from images and videos taken at sea using one of the state-of-the-art deep neural network-based object detection algorithms. A deep learning model is trained using a public maritime dataset, and results show it can detect all types of floating objects and classify them into ten specific classes that include a ship, speedboat, and buoy. The proposed deep learning model is compared to a universal trained model that detects and classifies objects into general classes, such as a person, dog, car, and boat, and results show that the proposed model outperforms the other in the detection of maritime objects. Different deep neural network structures are then compared to obtain the best detection performance. The proposed model also shows a real-time detection speed of approximately 30 frames per second. Hence, it is expected that the proposed model can be used to detect maritime objects and reduce risks while at sea.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.143-150
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• 2010

Markerless augmented reality system must have the capability to recognize and match natural objects both in indoor and outdoor environment. In this paper, a novel approach is proposed for extracting features and recognizing natural objects using visual descriptors and codebooks. Since the augmented reality applications are sensitive to speed of operation and real time performance, our work mainly focused on recognition of multi-class natural objects and reduce the computing time for classification and feature extraction. SIFT(scale invariant feature transforms) and SURF(speeded up robust feature) are used to extract features from natural objects during training and testing, and their performance is compared. Then we form visual codebook from the high dimensional feature vectors using clustering algorithm and recognize the objects using naive Bayes classifier.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.897-906
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• 2017

Projection Mapping, also known as Spatial Augmented Reality(SAR) has attracted much attention recently and used for many division, which can augment physical objects with projected various virtual replications. However, conventional approaches towards projection mapping have faced some limitations. Target objects' geometric transformation property does not considered, and movements of flexible objects-like paper are hard to handle, such as folding and bending as natural interaction. Also, precise registration and tracking has been a cumbersome process in the past. While there have been many researches on Projection Mapping on static objects, dynamic projection mapping that can keep tracking of a moving flexible target and aligning the projection at interactive level is still a challenge. Therefore, this paper propose a new method using Unity3D and ARToolkit for high-speed robust tracking and dynamic projection mapping onto non-rigid deforming objects rapidly and interactively. The method consists of four stages, forming cubic bezier surface, process of rendering transformation values, multiple marker recognition and tracking, and webcam real time-lapse imaging. Users can fold, curve, bend and twist to make interaction. This method can achieve three high-quality results. First, the system can detect the strong deformation of objects. Second, it reduces the occlusion error which reduces the misalignment between the target object and the projected video. Lastly, the accuracy and the robustness of this method can make result values to be projected exactly onto the target object in real-time with high-speed and precise transformation tracking.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.10
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• pp.67-75
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• 1997

A design for a system to perform rapid recognition of three dimensional objects is presented, focusing on efficient indexing. In order to retrieve the best matched models without exploring all possible object matches, we have employed a bayesian framework. A decision-theoretic measure of the discriminatory power of a feature for a model object is defined in terms of posterior probability. Detectability of a featrue defined as a function of the feature itselt, viewpoint, sensor charcteristics, nd the feature detection algorithm(s) is also considered in the computation of discribminatory power. In order to speed up the indexing or selection of correct objects, we generate and verify the object hypotheses for rfeatures detected in a scene in the order of the discriminatory power of these features for model objects.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.308-313
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• 2015

This paper describes a technique for complete identification of a two-dimensional scattering object and multiple objects immersed in air using microwaves where the scatterers are assumed to be a homogenous dielectric medium. The employed technique consists of initially retrieving the shape and position of the scattering object using a linear sampling method and then determining the electric permittivity and conductivity of the scatterer using adjoint sensitivity analysis. Incident waves are assumed to be TM (Transverse Magnetic) plane waves. This inversion algorithm results in high computational speed and efficiency, and it can be generalized for any scatterer structure. Also, this method is robust with respect to noise. The numerical results clearly show that this hybrid approach provides accurate reconstructions of various objects.

• Korean Journal of Computational Design and Engineering
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• v.5 no.1
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• pp.95-101
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• 2000

For last two decades numerous automatic mesh generation algorithms for various two dimensional objects have been introduced continuously and among them triangular mesh generation schemes have been majority because of efficiency and controllability. In our study, an existing triangular mesh generation algorithm developed by Lo is totally modified to more improve node distribution, element shape, and objects shape independency. ft is composed of node generation part and element generation part. In order to find a suitable node position within geometry, the suggested algorithm searches desirable positions of points within boundary and optimizes node position to generate comparatively well-shaped elements. More over, the suggested algorithm handles various complex two dimensional objects and its meshing speed shows superiority to those of the existing triangulation mesh generation algorithms. It is fully automated in a sense of constructing object boundary and hence can be directly used as an independent meshing software.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.109-116
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• 2023

This paper presents a network-based automation system for the detection of metallic objects in food and livestock. A metal detector is a core equipment used for the inspection required by HACCP. Since the existing metal detectors are manufactured as a single-body equipment, it is difficult to take into account various user requirements for the system. In order to overcome the drawback, this study presents a network-based automation system for metal detector utilizing an industrial fieldbus and modular components. The proposed system can effectively consider the various customer requirements and control schemes. The proposed system can also achieve the improvement in speed and success rate of detecting metallic objects. The effectiveness of the proposed system is demonstrated through a various experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2179-2182
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• 2005

Recently, optical 3D scanners are frequently used for inspection of parts, assembly and manufacturing tooling. One of the advantages is being able to measure a large area fast and accurately. Owing to recent advances in high-resolution image sensing technology, high power illumination technology, and high speed microprocessors, the accuracy and resolution of optical 3D scanners are being improved rapidly. In order to measure the entire geometry of objects, multiple scans have to be performed in various setups by moving either the objects or the scanner. This paper introduces novel methods to measure the entire geometry of objects by automatically changing the setups and then aligning the scanned data in a single coordinate system.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1097-1100
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• 1998

In this paper, the PLL(Phase-Locked Loops) for low voltage and high speed operation is described. In other to obtaining above objects, new CMOS circuit technologies have been used in the each block circuit of PLL. It operates with a lock range from 110 up to 700 MHz and has a peak to peak jitter of 50 ps at operating frequency of 250 MHz. It was fabricated in a $0.6\mu\textrm{m}$ CMOS technology and dissipated 45 mW from a single 3.3V.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.32-35
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• 2013

In this paper we proposed a PTZ camera system which automatically detect and track moving objects in the image. Once a moving object is detected the PTZ camera traces it in real-time. We proposed the control system which does not depend on camera focusing functionality but uses the object's center, moving direction, distance and speed. We implemented the system with the TI DM6446 DSP chip. The experimental result shows that the system has excellent performance for high speed vehicles.