• Journal of Broadcast Engineering
• /
• v.21 no.6
• /
• pp.861-877
• /
• 2016

This paper first discusses the disadvantages of the existing CamShift Algorithm for real time face tracking, and then proposes a new Camshift Algorithm that performs better than the existing algorithm. The existing CamShift Algorithm shows unstable tracking when tracing similar colors in the background of objects. This drawback of the existing CamShift is resolved by using Kinect’s pixel-by-pixel depth information and the Skin Detection algorithm to extract candidate skin regions based on HSV color space. Additionally, even when the tracking object is not found, or when occlusion occurs, the feature point-based matching algorithm makes it robust to occlusion. By applying the improved CamShift algorithm to face tracking, the proposed real-time face tracking algorithm can be applied to various fields. The results from the experiment prove that the proposed algorithm is superior in tracking performance to that of existing TLD tracking algorithm, and offers faster processing speed. Also, while the proposed algorithm has a slower processing speed than CamShift, it overcomes all the existing shortfalls of the existing CamShift.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.1
• /
• pp.27-32
• /
• 2013

It plays an important role to detect the shape of an ellipse in many application areas of image processing. But it is very difficult to detect the ellipse in the real image because the noise was involved in the image, other objects obscured the ellipse or the ellipses were overlap with each other. In this paper, we extract the boundary (edge) to detect ellipse in the image and perform the grouping process in order to reduce amount of information. As a result, the speed of the ellipse detection was improved. Also in order to the ellipse detection, we selected the five ellipse parameters at random And then to select the optimal parameters of the ellipse, the linear least-squares approximation is applied. To verify the ellipse detection, RANSAC algorithm is applied. After the algorithm proposed in this study was implemented, the results applied to the real images showed an aocuracy of 75% and speed was very fast to compared with other researches. It mean that the proposed algorithm was valuable to detect the ellipses in the image.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.2
• /
• pp.91-96
• /
• 2022

At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.

• Journal of Internet Computing and Services
• /
• v.22 no.2
• /
• pp.59-68
• /
• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.2
• /
• pp.205-214
• /
• 1997

In this paper, we suggest a cache mechanism to improve the speed fo query processing in distributed directory environment. For this, request and result and result about objects in remote site are store in the cache of local site. A cache mechanism developed through six phases; 1) Cached information which stored in distributed directory system is classified as application data, system data and meta data. 2) Cache system architecture is designed according to classified information. 3) Cache schema are designed for each cache information. 4) Least-TTL algorithms which use the weighted value of geograpical information and access frquency for replacements are developed for datacaches(application cache, system cache). 5) Operational algorithms are developed for meta data cache which has meta data tree. This tree is based on the information of past queries and improves the speed ofquery processing by reducing the scope of search space. 6) Finally, performance evaluations are performed by comparing with proposed cache mechanism and other mechanisms.

• Journal of the Korea Computer Graphics Society
• /
• v.21 no.3
• /
• pp.27-35
• /
• 2015

This study presents a volume rendering method using ambient occlusion which is one of global illumination methods. By considering the volume density distribution as normal distribution, ambient occlusion can be calculated at real-time speed regardless of modification of opacity transfer function. We calculate and store the averages and standard deviations of densities in a block centered at each voxel in pre-processing time. In rendering process, we determine the illumination value by estimating the nearby opacity. We generalized theoretical model and generated better quality images improving our previous research. In detail, various shapes of transfer function can be used due to the proposed equation model. Moreover, we introduced a multi-range model to give nearer objects more weight. As the result, more realistic volume rendering image can be generated at real-time speed by mixing local and ambient occlusion shading.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2019.11a
• /
• pp.264-264
• /
• 2019

The purpose of this paper is to establish development concepts for a novel collision avoidance system with preventing function of navigator's human error (Hu-CAS) in ship control behaviors. Hu-CAS consists of four modules: 1) collision risk assessment module to estimate collision priority between the ship and objects, 2) decision-making module to decide collision risk levels, 3) parameter estimation module needed in the ship control to avoid collisions and 4) control system to control the rudder angle and speed. Hu-CAS, proposed in this paper, can provide a novel system substitution current Autopilot and/or a CAS be teen manned vessel and Autonomous ship in a future.

• Journal of the Institute of Convergence Signal Processing
• /
• v.17 no.2
• /
• pp.83-92
• /
• 2016

In this paper, we introduce the results of the testing and observation systems for performance wideband expansion in the Korean VLBI Network(KVN). The KVN performs VLBI observations to 1024 Mbps data rate, and 8192 Mbps observing for four simultaneous observation is now evaluating for normal operation. The VLBI stations in several world countries developed their own wideband observing systems to observe the celestial objects with high precision and high resolution or are working with several countries. The KVN is planning to introduce a high-speed sampler, OCTAD, for sampling directly up to 2048 MHz bandwidth for RF signal of K/Q/W/D band in the frequency band without conversion. Therefore, as a preliminary study for the performance scalability of the KVN then through the close cooperation with National Astronomical Observatory of Japan (NAOJ), the OCTAD high-speed sampler and OCTADISK2 high-speed recorder were installed in the KVN Yonsei station, and verify the performance through a wideband.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.3-12
• /
• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.

• Korean Journal of Optics and Photonics
• /
• v.34 no.4
• /
• pp.139-150
• /
• 2023

Despite various light detection and ranging (LiDAR) architectures, it is very difficult to achieve long-range detection and high resolution in both vertical and horizontal directions with a wide field of view (FOV). The scanning architecture is advantageous for high-performance LiDAR that can attain long-range detection and high resolution for vertical and horizontal directions. However, a large-area photodetector (PD), which is disadvantageous for detection speed, is essentially required to secure the wide FOV. Thus we propose a PD based on the static unitary detector (STUD) technique that can operate multiple small-area PDs as a single large-area PD at a high speed. The InP/InGaAs STUD PIN-PD proposed in this paper is fabricated in various types, ranging from 1,256 ㎛×949 ㎛ using 32 small-area PDs of 1,256 ㎛×19 ㎛. In addition, we measure and analyze the noise and signal characteristics of the LiDAR receiving board, as well as the performance and sensitivity of various types of STUD PDs. Finally, the LiDAR receiving board utilizing the STUD PD is applied to a 3D scanning LiDAR prototype that uses a 1.5-㎛ master oscillator power amplifier laser. This LiDAR precisely detects long-range objects over 50 m away, and acquires high-resolution 3D images of 320 pixels×240 pixels with a diagonal FOV of 32.6 degrees simultaneously.