• Smart Media Journal
• /
• v.1 no.3
• /
• pp.36-42
• /
• 2012

Recently, the smart applications, such as smart phone and smart TV, become a hot issue in IT consumer markets. In particular, the smart TV provides 3D video services, hence efficient coding methods for 3D video data are required. Three-dimensional (3D) video involves stereoscopic or multi-view images to provide depth experience through 3D display systems. Binocular cues are perceived by rendering proper viewpoint images obtained at slightly different view angles. Since the number of viewpoints of the multi-view video is limited, 3D display devices should generate arbitrary viewpoint images using available adjacent view images. In this paper, after we explain a view synthesis method briefly, we propose a new algorithm to compensate view synthesis errors around object boundaries. We describe a 3D warping technique exploiting the depth map for viewpoint shifting and a hole filling method using multi-view images. Then, we propose an algorithm to remove boundary noises that are generated due to mismatches of object edges in the color and depth images. The proposed method reduces annoying boundary noises near object edges by replacing erroneous textures with alternative textures from the other reference image. Using the proposed method, we can generate perceptually inproved images for 3D video systems.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.43 no.6 s.348
• /
• pp.9-17
• /
• 2006

We proposed a new High-speed CMOS Level Up/Down Shifter circuits that can be used with Dynamic Voltage and Frequency Scaling(DVFS) algorithm, for low power system in the SoC(System-on-Chip). This circuit used to interface between the other voltage levels in each CMOS circuit boundary, or between multiple core voltage levels in a system bus. Proposed circuit have advantage that decrease speed attenuation and duty ratio distortion problems for interface. The level up/down shifter of the proposed circuit designed that operated from multi core voltages$(0.6\sim1.6V)$ to used voltage level for each IP at the 500MHz input frequency The proposed circuit supports level up shifting from the input voltage levels, that are standard I/O voltages 1.8V, 2.5V, 3.3V, to multiple core voltage levels in between of $0.6V\sim1.6V$, that are used internally in the system. And level down shifter reverse operated at 1Ghz input frequency for same condition. Simulations results are shown to verify the proposed function by Hspice simulation, with $0.6V\sim1.6V$ CMOS Process, $0.13{\mu}m$ IBM CMOS Process and $0.65{\mu}m$ CMOS model parameters. Moreover, it is researched delay time, power dissipation and duty ration distortion of the output voltage witch is proportional to the operating frequency for the proposed circuit.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.21-35
• /
• 2018

Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.10
• /
• pp.2619-2627
• /
• 2009

The ground fault is occupying 70% among the total number of faults in ungrounded distribution power system. When the ground fault occurs in ungrounded system, the fault current is so small that it is hard to detect. But fault handling is very important because to continue power supply during fault conditions may cause the fault spreading and the distribution device in trouble. This paper presents the fault line detection method by using GPT signal detecting zero sequence voltage, and the fault section detection method by detecting whether GPT signal is disappeared or not during shifting normally open switch, which is connecting switch between distribution lines with open state in order to restore the outage area under emergency situation, and during isolating each section one by one which belongs to the fault line. This method is efficient because there is no whole power interruption during the fault section detection, and it is possible to perform both the fault section detection and the service restoration for the outage area at the same time, and it can apply to various distribution system configuration. Program for the fault restoration was developed applying proposed method, and it has been validated by applying to the pilot project of distribution automation system in Vietnam which has the ungrounded distribution system.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.12
• /
• pp.17-26
• /
• 1998

Ultrasonic sensors are widely used in various applications due to advantages of low cost, simplicity in construction, mechanical robustness, and little environmental restriction in usage. But for the application of object recognition, ultrasonic sensors exhibit several shortcomings of poor directionality which results in low spatial resolution of objects, and specularity which gives frequent erroneous range readings. The time-of-flight(TOF) method generally used for distance measurement can not distinguish small object patterns of plane, corner or edge. To resolve the problem, an increased number of the sensors in the forms of a linear array or 2-dimensional array of the sensors has been used. Also better resolution has been obtained by shifting the array in several steps using mechanical actuators. Also simple patterns are classified based on analyzing signal reflections. In this paper we propose a method of a sensor array system with improved capability in pattern distinction using electronic circuits accompanying the sensor array, and intelligent algorithm based on neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. A set of different return signals from neighborhood sensors is manipulated to provide enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.14 no.5
• /
• pp.19-30
• /
• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• Journal of Internet Computing and Services
• /
• v.22 no.1
• /
• pp.109-135
• /
• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of Korea Water Resources Association
• /
• v.56 no.6
• /
• pp.403-417
• /
• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.