• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.243-246
• /
• 2002

The proliferation of digitized media(audio, image and video) is creating a processing need for copyright enforcement schemes that protect copyright ownership. we argue that a watermark must be placed in perceptually significant components of a signal if it is to be robust to signal distortions and malicious attack. In this paper, RGB coordinate image is transformed into LUV coordinate, it include the characteristics of, Human vision and then the UV component is transformed into NxN block DCT transform. we propose a technique for embedding the watermark of visually recognizable mark into the middle frequency domain of image.

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.2
• /
• pp.74-81
• /
• 2005

As the multimedia data increases, various scene change detection algorithms for video indexing and sequence matching have been proposed to efficiently manage and utilize digital media. In this paper, we propose a robust scene change detection algorithm for video sequences with abrupt luminance variations. To improve the accuracy and to reduce the computational complexity of video indexing with abrupt luminance variations, the proposed algorithm utilizes edge features as well as color features, which yields a remarkably better performance than conventional algorithms. In the proposed algorithm first we extract the candidate shot boundaries using color histograms and then determine using edge matching and luminance compensation if they are shot boundaries or luminance changes. If the scene contains trivial brightness variations, the edge matching and luminance compensation are performed only for shot boundaries. In experimental results, the proposed method gives remarkably a high performance and efficiency than the conventional methods with the similar computational complexity.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.4
• /
• pp.232-237
• /
• 2019

It has recently been combined with advanced technologies such as AR and VR, and its application range is expanding to various forms of smart signage. However, until now, digital signage service that reaches us is installed in many floating populations such as bus stops, elevators, and banks and is used in the form of providing news, weather, and advertisements. In addition, large companies, government offices, and outdoor advertising companies occupy the market. The use of such services in small and medium-sized businesses and small retail stores is costly and expensive to manage. Also, it is difficult to generalize the market because services and solutions are being deployed in the market in the form of top-down. Therefore, in this paper, we proposed a digital signage system for transmitting a remote video advertisement that uses a show window in front of the store as a beam project screen for small retail stores, and can remotely set and manage and update it in OSGi service platform.

• Journal of the Institute of Convergence Signal Processing
• /
• v.7 no.4
• /
• pp.207-213
• /
• 2006

This paper presents the design and implementation of a video processor for the device of need TV-OUT function. The designed video processor satisfies the standard conditions of ITU-R(International Telecommunication Union-Radiocommunication) BT.470. Also, in order to apply various digital device, we concentrate upon hardware complexity. ITU-R BT.470 can be classified as NTSC, PAL or SECAM. NTSC and PAL use QAM(Quardarature Amplitude Modulation) to transmit color difference signals and SECAM uses FM(Frequency Modulation). FM must have antic-cloche filter but filter recommended by ITU-R BT.470 is not easy to design due to sharpness of the frequency response. So this paper proposes that the special quality of anti-cloche filter is transformed easy to design and the modulation method is modified to be identical with the result required at standard. The processor can control power consumption by output mode to apply portable digital devices. The proposed processor is experimentally demonstrated with ALTERA FPGA APEX20KE EP20K1000EBC652-3 device and SAMSUNG LCD-TV.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4160-4176
• /
• 2015

Data compression like image and video compression has come a long way since the introduction of Compressive Sensing (CS) which compresses sparse signals such as images, videos etc. to very few samples i.e. M < N measurements. At the receiver end, a robust and efficient recovery algorithm estimates the original image or video. Many prominent algorithms solve least squares problem (LSP) iteratively in order to reconstruct the signal hence consuming more processing time. In this paper non-iterative threshold based recovery algorithm (NITRA) is proposed for the recovery of images and videos without solving LSP, claiming reduced complexity and better reconstruction quality. The elapsed time for images and videos using NITRA is in ㎲ range which is 100 times less than other existing algorithms. The peak signal to noise ratio (PSNR) is above 30 dB, structural similarity (SSIM) and structural content (SC) are of 99%.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.2
• /
• pp.91-95
• /
• 2004

In this paper, we propose a fuzzy controller for the evaluation of the quantization parameters in the H.263 coder. Our method adopts the Mamdani method for fuzzification and adopts the centroid method for defuzzification respectively. The inputs are variance, entropy in the spatial domain, current motion vector and previous motion vector in the temporal. Fuzzy variables are determined to be compatible in visual characteristics and fuzzy membership function is induced and then, FAM banks are designed to reduce the number of rules. In this paper, fuzzy quantization has been applied to a practical video compression. This results show that the quality of decode image enhances and the rate control method using fuzzy quantization is effective.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.2
• /
• pp.77-82
• /
• 2012

This paper presents a hardware-implemented face regions stabilization algorithm that stabilizes facial regions using the locations and sizes of human faces found by a face detection system. Face detection algorithms extract facial features or patterns determining the presence of a face from a video source and detect faces via a classifier trained on example faces. But face detection results has big variations in the detected locations and sizes of faces by slight shaking. To address this problem, the high frequency reduce filter that reduces variations in the detected face regions by taking into account the face range information between the current and previous video frames are implemented in addition to center distance comparison and zooming operations.

• Journal of Information Processing Systems
• /
• v.17 no.4
• /
• pp.754-771
• /
• 2021

In the task of continuous dimension emotion recognition, the parts that highlight the emotional expression are not the same in each mode, and the influences of different modes on the emotional state is also different. Therefore, this paper studies the fusion of the two most important modes in emotional recognition (voice and visual expression), and proposes a two-mode dual-modal emotion recognition method combined with the attention mechanism of the improved AlexNet network. After a simple preprocessing of the audio signal and the video signal, respectively, the first step is to use the prior knowledge to realize the extraction of audio characteristics. Then, facial expression features are extracted by the improved AlexNet network. Finally, the multimodal attention mechanism is used to fuse facial expression features and audio features, and the improved loss function is used to optimize the modal missing problem, so as to improve the robustness of the model and the performance of emotion recognition. The experimental results show that the concordance coefficient of the proposed model in the two dimensions of arousal and valence (concordance correlation coefficient) were 0.729 and 0.718, respectively, which are superior to several comparative algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.8
• /
• pp.2851-2865
• /
• 2014

To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

• ETRI Journal
• /
• v.31 no.1
• /
• pp.1-9
• /
• 2009

Frequency domain analysis is a fundamental procedure for understanding the characteristics of visual data. Several studies have been conducted with 2D videos, but analysis of stereoscopic 3D videos is rarely carried out. In this paper, we derive the Fourier transform of a simplified 3D video signal and analyze how a 3D video is influenced by disparity and motion in terms of temporal aliasing. It is already known that object motion affects temporal frequency characteristics of a time-varying image sequence. In our analysis, we show that a 3D video is influenced not only by motion but also by disparity. Based on this conclusion, we present a temporal anti-aliasing filter for a 3D video. Since the human process of depth perception mainly determines the quality of a reproduced 3D image, 2D image processing techniques are not directly applicable to 3D images. The analysis presented in this paper will be useful for reducing undesirable visual artifacts in 3D video as well as for assisting the development of relevant technologies.