• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.597-606
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• 2020

Because the USV(Unmanned Surface Vehicle) is capable of remote control or autonomous navigation at sea, it can secure the superiority of combat power while minimizing human losses in a future combat environment. To plan the technology for the development of USV, the trend analysis of related technology and the selection of promising technology should be preceded, but there has been little research in this area. The purpose of this paper was to measure and evaluate the technology trends quantitatively. For this purpose, this study analyzed the technology trends and selected promising/declining technologies using topic modeling of papers and patent data. As a result of topic modeling, promising technologies include control and navigation, verification/validation, autonomous level, mission module, and application technology, and declining technologies include underwater communication and image processing technology. This study also identified new technology areas that were not included in the existing technology classification, e.g., technology related to research and development of USV, artificial intelligence, launch/recovery, and operation, such as cooperation with manned and unmanned systems. The technology trends and new technology areas identified through this study may be used to derive key technologies related to the development of the USV and establish appropriate R&D policies.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.48-60
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• 2007

In previous researches for iris feature extraction, they transform a original iris image into rectangular one by stretching and interpolation, which causes the distortion of iris patterns. Consequently, it reduce iris recognition accuracy. So we are propose the method that extracts iris feature by using polar coordinates without distortion of iris patterns. Our proposed method has three strengths compared with previous researches. First, we extract iris feature directly from polar coordinate circular iris image. Though it requires a little more processing time, there is no degradation of accuracy for iris recognition and we compares the recognition performance of polar coordinate to rectangular type using by Hamming Distance, Cosine Distance and Euclidean Distance. Second, in general, the center position of pupil is different from that of iris due to camera angle, head position and gaze direction of user. So, we propose the method of iris feature detection based on polar coordinate circular iris region, which uses pupil and iris position and radius at the same time. Third, we overcome override point from iris patterns by using polar coordinates circular method. each overlapped point would be extracted from the same position of iris region. To overcome such problem, we modify Gabor filter's size and frequency on first track in order to consider low frequency iris patterns caused by overlapped points. Experimental results showed that EER is 0.29%, d' is 5,9 and EER is 0.16%, d' is 6,4 in case of using conventional rectangular image and proposed method, respectively.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.439-446
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• 2014

An amphibious inspection robot system (hereafter AIROS) is being developed to visually inspect the in-containment refueling storage water tank (hereafter IRWST) strainer in APR1400 instead of a human diver. Four IRWST strainers are located in the IRWST, which is filled with boric acid water. Each strainer has 108 sub-assembly strainer fin modules that should be inspected with the VT-3 method according to Reg. guide 1.82 and the operation manual. AIROS has 6 thrusters for submarine voyage and 4 legs for walking on the top of the strainer. An inverse kinematic algorithm was implemented in the robot controller for exact walking on the top of the IRWST strainer. The IRWST strainer has several top cross braces that are extruded on the top of the strainer, which can be obstacles of walking on the strainer, to maintain the frame of the strainer. Therefore, a robot leg should arrive at the position beside the top cross brace. For this reason, we used an image processing technique to find the top cross brace in the sole camera image. The sole camera image is processed to find the existence of the top cross brace using the cross edge detection algorithm in real time. A 5-DOF robot arm that has multiple camera modules for simultaneous inspection of both sides can penetrate narrow gaps. For intuitive presentation of inspection results and for management of inspection data, inspection images are stored in the control PC with camera angles and positions to synthesize and merge the images. The synthesized images are then mapped in a 3D CAD model of the IRWST strainer with the location information. An IRWST strainer mock-up was fabricated to teach the robot arm scanning and gaiting. It is important to arrive at the designated position for inserting the robot arm into all of the gaps. Exact position control without anchor under the water is not easy. Therefore, we designed the multi leg robot for the role of anchoring and positioning. Quadruped robot design of installing sole cameras was a new approach for the exact and stable position control on the IRWST strainer, unlike a traditional robot for underwater facility inspection. The developed robot will be practically used to enhance the efficiency and reliability of the inspection of nuclear power plant components.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.64-70
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• 2011

Portable artificial electronic nose (E-nose) system suffers from noisy fluctuation in surroundings such as temperature, vapor concentration, and gas flow, because its measuring condition is not controled precisely as in the laboratory. It is important to develop a simple and robust vapor recognition technique applicable to this uncontrolled measurement, especially for the portable measuring and diagnostic system which are expanding its area with the improvements in micro bio sensor technology. This study used a PDA-based portable E-nose to collect the uncontrolled vapor measurement signals, and applied the image matching algorithm developed in the previous study on the measured signal to verify its robustness and improved accuracy in portable vapor recognition. The results showed not only its consistent performance under noisy fluctuation in the portable measurement signal, but also an advanced recognition accuracy for 2 similar vapor species which have been hard to discriminate with the conventional maximum sensitivity feature extraction method. The proposed method can be easily applied to the data processing of the ubiquitous sensor network (USN) which are usually exposed to various operating conditions. Furthermore, it will greatly help to realize portable medical diagnostic and environment monitoring system with its robust performance and high accuracy.

• The Journal of Bigdata
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• v.5 no.1
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• pp.29-39
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• 2020

Purpose The atmosphere of respect for individual tastes that have spread throughout society has changed the consumption trend. As a result, the travel industry is also seeing customized travel as a new trend that reflects consumers' personal tastes. In particular, there is a growing interest in 'film-induced tourism', one of the areas of travel industry. We hope to satisfy the individual's motivation for traveling while watching movies with customized travel proposals, which we expect to be a catalyst for the continued development of the 'film-induced tourism industry'. Design/methodology/approach In this study, we implemented a methodology through 'OCR' of extracting and suggesting film location information that viewers want to visit. First, we extract a scene from a movie selected by a user by using 'OpenCV', a real-time image processing library. In addition, we detected the location of characters in the scene image by using 'EAST model', a deep learning-based text area detection model. The detected images are preprocessed by using 'OpenCV built-in function' to increase recognition accuracy. Finally, after converting characters in images into recognizable text using 'Tesseract', an optical character recognition engine, the 'Google Map API' returns actual location information. Significance This research is significant in that it provides personalized tourism content using fourth industrial technology, in addition to existing film tourism. This could be used in the development of film-induced tourism packages with travel agencies in the future. It also implies the possibility of being used for inflow from abroad as well as to abroad.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.249-256
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• 2011

Finding a new set of features representing textured images is one of the most important studies in textured image analysis. This is because it is impossible to construct a perfect set of features representing every textured image, and it is inevitable to choose some relevant features which are efficient to on-going image processing jobs. This paper intends to find relevant features which are efficient to textured image segmentation. In this regards, this paper presents a different method for the segmentation of textured images based on the Gabor filter. Gabor filter is known to be a very efficient and effective tool which represents human visual system for texture analysis. Filtering a real-valued input image by the Gabor filter results in complex-valued output data defined in the spatial frequency domain. This complex value, as usual, gives the module and the phase. This paper focused its attention on the phase information, rather than the module information. In fact, the module information is considered very useful at region analysis in texture, while the phase information was considered almost of no use. But this paper shows that the phase information can also be fully useful and effective at region analysis in texture, once a good method introduced. We now propose "phase derivated method", which is an efficient and effective way to compute the useful phase information directly from the filtered value. This new method reduces effectively computing burden and widen applicable textured images.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Korean Chemical Engineering Research
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• v.52 no.3
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• pp.382-387
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• 2014

The PC/ABS blends were manufactured with high shear rate processing. Changes of the blend morphology were analyzed according to the screw speed and processing time. To find optimal conditions of the high shear rate processing of the PC/ABS blend, blend morphology and size of the dispersed phase, ABS, were observed with a SEM. Also, tensile properties of the PC/ABS blends were measured to investigate the effect of the high shear rate process with the screw speed of 500 rpm to 3000 rpm for processing times of 10s to 40s. Especially, to observe the dispersed phase of the PC/ABS blend clearly, fracture surfaces of the PC/ABS blend were etched with chromic acid solution. As screw speed and processing time increase, dispersed phase size of the PC/ABS blend decreases and mechanical properties of the blend decrease as well. Especially, at screw speed over than 1000 rpm of high shear rate processing, mechanical properties of the PC/ABS blends decrease drastically due to the degradation of the blend during the high shear rate processing. Consequently, the optimal condition of screw speed of the high shear processing of the PC/ABS blend is set at 1000rpm, in this study. Under optimal condition, the PC/ABS blend has relatively high mechanical properties with the relatively stable micro-structure having nanometer scale dispersed phase.