• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.145-147
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• 2006

Image resizing is to change an image size by upsampling or downsampling of a digital image. Most still images and video frames are given in a compressed domain on digital media. Image resizing of a compressed image can be performed in a spatial domain via decompression or recompression. In general, resizing of a compressed image in a compressed domain is much faster than that in a spatial domain. In this paper, we propose an approach to resize images in the integer discrete cosine transform (DCT) domain, which exploits the multiplication-convolution property of DCT.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.458-471
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• 2006

Digital watermarking of multimedia data is a very active research area that has enjoyed a considerable amount of attention in recent years. In this paper, we propose an algorithm for embedding/detecting a fragile watermark in MPEG-4 compressed video domain (Simple and Advance Simple Profiles). The watermark bits are put directly into Huffman VLC-codespace of quantized DCT domain. The advantage of watermark embedding into the compressed domain is the significant savings for a real-time implementation as it does not require a full decoding operation. The watermark embedding does not change the video file size. The algorithm demonstrates high watermarking capacity, thereby providing reliable foolproof authentication. The results of experimental testing demonstrate that watermark embedding preserves the video quality. Watermark detection is performed without using the original video.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.375-382
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• 2009

This paper proposes a new audio fingerprinting method based on compressed-domain features. By basing on the compressed domain, the computational efficiency of the proposed method can be greatly enhanced. Especially we deal with MDCT domain, which is widely employed in audio compression, and extract three kinds of subband features; energy, centroid, and flatness. By taking signs after differentially filtering each feature, binary audio fingerprints are obtained. The identification performance of the three kinds of fingerprints are experimentally compared. Among the considered compressed-domain subband features, the subband energy showed the best performance for fingerprinting.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.6
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• pp.503-511
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• 2014

In this paper, a novel, real-time video stitching algorithm in an H.264/AVC compressed domain is proposed. This enables viewers to watch multiple video contents using a single device. The basic concept of this paper is that the server is asked to combine multiple streams into one bit-stream based in a compressed domain. In other words, this paper presents a new compressed domain combiner that works in boundary macroblocks of input videos with re-calculating intra prediction mode, intra prediction MVD, a re-allocation of the coefficient table, and border extension methods. The rest of the macroblocks of the input video data are achieved simply by copying them. Simulation experiments have demonstrated the possibility and effectiveness of the proposed algorithm by showing that it is able to generate more than 103 frames per second, stitching four 480p-sized images into each frame.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.157-160
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• 2002

Scene change detection is the fundamental process of automatic video indexing and retrieving. In this paper we propose a method which utilizes both compressed and uncompressed domain methods to detect scene change in a video. Candidate locations for scene change are estimated from DC images and motion vector information in compressed domain. And candidate frames are verified using edge histogram distance and color histogram distance, in uncompressed domain. The experimental results show that scene change can be detected fast and correctly by proposed method.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.21-23
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• 2006

Due to development of Internet network environments and data compression techniques, the size and amount of multimedia data has greatly increased. They are compressed before transmission or storage. Dealing with these compressed data such as video retrieval or indexing requires the decoding procedure most of the time. In video retrieval and indexing a color histogram is one of the most frequently used tools. We propose a novel scheme for extracting color histograms from images transformed into the compressed domain using $8{times}8$ DCT(Discrete Cosine Transform). In this scheme an averaged version of original image is obtained by filtering DCT coefficients with a filter we destined.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.8
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• pp.369-374
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• 2006

Due to development of internet network environments and data compression techniques, the size and amount of multimedia data has greatly increased. They are compressed before transmission or storage. Dealing with these compressed data such as video retrieval or indexing requires decompression procedure in most cases. This causes additional computations and increases the processing time. In various applications a histogram is one of the most frequently used tools. Efficiency of extracting such histograms will drop down if decompression is involved. We propose a novel scheme for extracting histograms from images that are transformed into the compressed domain by 8x8 DCT(Discrete Cosine Transform). In this scheme an averaged version of original image is obtained by a simple linear combination of DCT coefficients with the sets of coefficients we designed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.58-78
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• 2016

Compressed sensing (CS) possesses the potential benefits for spectrum sensing of wideband signal in cognitive radio. The sparsity of signal in frequency domain denotes the number of occupied channels for spectrum sensing. This paper presents a scheme of adaptively adjusting the number of compressed measurements to reduce the unnecessary computational complexity when priori information about the sparsity of signal cannot be acquired. Firstly, a method of sparsity estimation is introduced because the sparsity of signal is not available in some cognitive radio environments, and the relationship between the amount of used data and estimation accuracy is discussed. Then the SNR of the compressed signal is derived in the closed form. Based on the SNR of the compressed signal and estimated sparsity, an adaptive algorithm of adjusting the number of compressed measurements is proposed. Finally, some simulations are performed, and the results illustrate that the simulations agree with theoretical analysis, which prove the effectiveness of the proposed adaptive adjusting of compressed measurements.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.433-439
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• 2016

In this paper, we propose a optimized steganography how to improve the image degradation of the existing data hiding techniques. This method operates in the compressed domain(JPEG) of an image. Most of the current information concealment methods generally change the coefficients to hide information. And several methods have tried to improve the performance of a typical steganography method such as F5 including a matrix encoding. Those papers achieved the object of reducing the distortion which is generated as hiding data in coefficients of compressed domain. In the proposed paper we analyzed the effect of the quantization table for hiding the data in the compressed domain. As a result, it found that can decrease the distortion that occur in the application of steganography techniques. This paper provides a little (Maximum: approximately 6.5%) further improved results in terms of image quality in a data hiding on compressed domain. Developed algorithm help improve the data hiding performance of compressed image other than the JPEG.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.10-17
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• 2009

This paper proposes a compressed domain signature extraction method which can be used for CBCD (Content Based Copy Detection). Since existing signature extraction methods for the CBCD are executed in spatial domain, they need additional computations to decode the compressed video before the signature extraction. To avoid this overhead, we generate a thumbnail image directly from the compressed video without full decoding. Then we can extract the video signature from the thumbnail image. Experimental results of extracting brightness ordering information as the signature for CBCD show that our proposed method is 2.8 times faster than the spatial domain method while maintaining 80.98% accuracy.