• Journal of Broadcast Engineering
• /
• v.22 no.2
• /
• pp.214-233
• /
• 2017

For people with physical or sensory limitations, broadcasting is the main means of information acquisition and leisure. Recently, changes in the media environment, such as convergence of broadcasting and communication, digital mobile conversion of broadcasting, and active media usage behavior of users, make broadcasting accessibility of the disabled difficult, and as a result, the information gap between the disabled and the non-disabled is increasing. A notice on broadcasting rights for the disabled was enacted in consequence of the amendment of the Broadcasting Law in July 2011 and the web accessibility guideline became more effective with the amendment of the National Informatization Act in 2013 so that legal basis for the right of media access for the disabled was established. However, media services for them are still lacking quantitatively and qualitatively. In this study, we describe the present status of the audio description service for the visually impaired, and analyze the results of the questionnaire survey on the usage status, satisfaction and improvement requirements of the audio description service for 100 visually impaired people.

• Journal of Broadcast Engineering
• /
• v.13 no.5
• /
• pp.732-743
• /
• 2008

In H.264/AVC, 4$\times$4 block transform is used for intra and inter prediction instead of 8$\times$8 block transform. Using small block size coding, H.264/AVC obtains high temporal prediction efficiency, however, it has limitation in utilizing spatial redundancy. Motivated on these points, we propose a multi-dimensional transform which achieves both the accuracy of temporal prediction as well as effective use of spatial redundancy. From preliminary experiments, the proposed multi-dimensional transform achieves higher energy compaction than 2-D DCT used in H.264. We designed an integer-based transform and quantization coder for multi-dimensional coder. Moreover, several additional methods for multi-dimensional coder are proposed, which are cube forming, scan order, mode decision and updating parameters. The Context-based Adaptive Variable-Length Coding (CAVLC) used in H.264 was employed for the entropy coder. Simulation results show that the performance of the multi-dimensional codec appears similar to that of H.264 in lower bit rates although the rate-distortion curves of the multi-dimensional DCT measured by entropy and the number of non-zero coefficients show remarkably higher performance than those of H.264/AVC. This implies that more efficient entropy coder optimized to the statistics of multi-dimensional DCT coefficients and rate-distortion operation are needed to take full advantage of the multi-dimensional DCT. There remains many issues and future works about multi-dimensional coder to improve coding efficiency over H.264/AVC.

• Journal of Broadcast Engineering
• /
• v.22 no.3
• /
• pp.295-312
• /
• 2017

Digital video content is the most information-intensive and high-value content. Therefore, it is necessary to protect the intellectual property rights of these contents, and this paper also proposes a watermarking method of digital image for this purpose. The proposed method uses the frequency characteristics of 2-Dimensional Discrete Wavelet Transform (2D-DWT) for digital images and digital watermark on global data without using local or specific data of the image for watermark embedding. The method to insert digital watermark data uses a simple Quantization Index Modulation (QIM) and a multiple watermarking method that inserts the same watermark data in multiple. When extracting a watermark, multiple watermarks are extracted and the final watermark data is determined by a simple statistical method. This method is an empirical method for experimentally determining the parameters in the watermark embedding process. The proposed method performs experiments on various images against various attacks and shows the superiority of the proposed method by comparing the performance with the representative existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.5
• /
• pp.914-923
• /
• 2015

Recently, as the number of smart devices (such as smart TV or Web based IPTV) increases, the way of digital broadcast contents is changed. This change leads that conventional broadcast media accepts Web platform and its services to provide more quality contents. Based on this change, in education field, education broadcasting also follows the trend. The traditional education broadcasting platforms, which just delivered the lecture in one-way, are utilized the Web technology to make interaction between teacher and student. Current education platforms, however, are insufficient to satisfy users' demands for two-way interactions. This paper proposes a new remote collaborative learning platform which able to provide high interactivity among users. Based on new functional requirements from original use case, the platform provides collaborative contents sharing and collaborative video streaming techniques by utilizing WebRTC (Web Real-Time Communication) technology. The implementation demonstrates the operability of proposed system.

• Journal of Broadcast Engineering
• /
• v.17 no.1
• /
• pp.165-178
• /
• 2012

In most conventional video codecs, such as MPEG-2 and MPEG-4, inter coding is performed with the fixed motion vector resolution. When KTA software was developed, resolution for MVs can be selected in each slice. Although KTA codec uses a variety of resolutions for ME, the selected resolution is applied over the entire pixels in the slice and the statistical property of the local area is not considered. In this paper, we propose an adaptive decision scheme for motion vector resolution which depends on region, where MV search area is divided to multiple regions according to the distance from PMV. In each region, the assigned resolution is used to estimate MV. Each region supports different resolution for ME from other regions. The efficiency of the proposed scheme is affected from threshold values to divide the search area and the entropy coding method to encode the estimated MV. Simulation results with HM3.0 which is the reference software of HEVC show that the proposed scheme provides bit rate gains of 0.9%, 0.6%, and 2.9% in Random Access, Low Delay with B picture, and Low Delay with P picture structures, respectively.

• Journal of Broadcast Engineering
• /
• v.17 no.1
• /
• pp.152-164
• /
• 2012

DMB provides various kinds of data services such as BWS and TPEG service in addition to audio and video services. But recently the necessity of new business models creating profit has been on the rise due to the saturation of DMB receiver market and break-down of market barrier between mobile IPTV and DMB services. This paper introduces DMB filecasting service technology, which can be expected a new profit-creative business model. The purpose of DMB filecasting service is to transmit non-real time multimedia contents based on DMB AF format to the users through DMB channels. It makes possible to consume DMB contents with any DMB-installed device anytime, anywhere and share them with others. Also DMB filecasting service makes consumption and request of DMB contents possible to be extented to a variety of networks as well as DMB channels. The paper explains the standardization status of DMB filecasting service and various DMB filecasting service scenarios. And also it proposes a signalling methode, a transmission and reception protocol and a receiver structure using DMB broadcasting program guide information.

• Journal of Broadcast Engineering
• /
• v.12 no.6
• /
• pp.611-623
• /
• 2007

The H.264|AVC standard incorporates an intra prediction tool into inter frame coding. However, this leads to excessive amount of increase in encoding time, thus resulting in the difficulty in real-time implementation of software encoders. In this paper, we first propose an early decision on intra prediction coding and a fast intra prediction method using the characteristics of block contents and the context of neighboring block modes for the intra prediction in the inter frame coding of H.264/AVC. Basically, the proposed methods determine a skip condition on whether the $4{\times}4$ intra prediction is to be used in the inter frame coding by considering the content characteristics of each block to be encoded and the context of its neighboring blocks. The performance of our proposed methods is compared with the Joint Model reference software version 11.0 of H.264|AVC. The experimental results show that our proposed methods allow for 41.63% reduction in the total encoding time with negligible amounts of PSNR drops and bitrate increases, compared to the original Joint Model reference software version 11.0.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.1076-1084
• /
• 2019

In this paper, we introduced a system that extracts metadata by recognizing characters and objects in media using deep learning technology. In the field of broadcasting, multimedia contents such as video, audio, image, and text have been converted to digital contents for a long time, but the unconverted resources still remain vast. Building media archives requires a lot of manual work, which is time consuming and costly. Therefore, by implementing a deep learning-based metadata generation system, it is possible to save time and cost in constructing media archives. The whole system consists of four elements: training data generation module, object recognition module, character recognition module, and API server. The deep learning network module and the face recognition module are implemented to recognize characters and objects from the media and describe them as metadata. The training data generation module was designed separately to facilitate the construction of data for training neural network, and the functions of face recognition and object recognition were configured as an API server. We trained the two neural-networks using 1500 persons and 80 kinds of object data and confirmed that the accuracy is 98% in the character test data and 42% in the object data.

• Journal of Broadcast Engineering
• /
• v.24 no.5
• /
• pp.713-725
• /
• 2019

Automatic License Plate Recognition (ALPR) is a technology required for many applications such as Intelligent Transportation Systems and Video Surveillance Systems. Most of the studies have studied were about the detection and recognition of license plates on cars, and there is very little about detecting and recognizing license plates on motorbikes. In the case of a car, the license plate is located at the front or rear center of the vehicle and is a straight or slightly sloped license plate. Also, the background of the license plate is mainly monochromatic, and license plate detection and recognition process is less complicated. However since the motorbike is parked by using a kickstand, it is inclined at various angles when parked, so the process of recognizing characters on the motorbike license plate is more complicated. In this paper, we have developed a 2-stage YOLOv2 algorithm to detect the area of a license plate after detection of a motorbike area in order to improve the recognition accuracy of license plate for motorbike data set parked at various angles. In order to increase the detection rate, the size and number of the anchor boxes were adjusted according to the characteristics of the motorbike and license plate. Image warping algorithms were applied after detecting tilted license plates. As a result of simulating the license plate character recognition process, the proposed method had the recognition rate of license plate of 80.23% compared to the recognition rate of the conventional method(YOLOv2 without image warping) of 47.74%. Therefore, the proposed method can increase the recognition of tilted motorbike license plate character by using the adjustment of anchor boxes and the image warping which fit the motorbike license plate.

• Journal of Broadcast Engineering
• /
• v.26 no.3
• /
• pp.296-307
• /
• 2021

A digital hologram (DH) is an ultra-high value-added video content that includes 3D information in 2D data. Therefore, its intellectual property rights must be protected for its distribution. For this, this paper proposes a watermarking method of DH using a deep neural network. This method is a watermark (WM) invisibility, attack robustness, and blind watermarking method that does not use host information in WM extraction. The proposed network consists of four sub-networks: pre-processing for each of the host and WM, WM embedding watermark, and WM extracting watermark. This network expand the WM data to the host instead of shrinking host data to WM and concatenate it to the host to insert the WM by considering the characteristics of a DH having a strong high frequency component. In addition, in the training of this network, the difference in performance according to the data distribution property of DH is identified, and a method of selecting a training data set with the best performance in all types of DH is presented. The proposed method is tested for various types and strengths of attacks to show its performance. It also shows that this method has high practicality as it operates independently of the resolution of the host DH and WM data.