• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.364-366
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• 2005

From the 90's, the image information retrieval methods have been on progress. As good examples of the methods, Conventional histogram method and merged-color histogram method were introduced. They could get good result in image retrieval. However, Conventional histogram method has disadvantages if the histogram is shifted as a result of intensity change. Merged-color histogram, also, causes more process so, it needs more time to retrieve images. In this paper, we propose an improved new method using Adaptive Color Histogram Bin Matching(AHB) in image retrieval. The proposed method has been tested and verified through a number of simulations using hundreds of images in a database. The simulation results have Quickly yielded the highly accurate candidate images in comparison to other retrieval methods. We show that AHB's can give superior results to color histograms for image retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5592-5609
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• 2017

JPEG steganography detection is an active research topic in the field of information hiding due to the wide use of JPEG image in social network, image-sharing websites, and Internet communication, etc. In this paper, a new steganalysis method for content-adaptive JPEG steganography is proposed by integrating the evolutionary feature selection and classifier ensemble selection. First, the whole framework of the proposed steganalysis method is presented and then the characteristic of the proposed method is analyzed. Second, the feature selection method based on genetic algorithm is given and the implement process is described in detail. Third, the method of classifier ensemble selection is proposed based on Pareto evolutionary optimization. The experimental results indicate the proposed steganalysis method can achieve a competitive detection performance by compared with the state-of-the-art steganalysis methods when used for the detection of the latest content-adaptive JPEG steganography algorithms.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.6
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• pp.635-642
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• 2000

In this paper, we proposed an efficient document conversion mechanism to provide a adaptive web document to mobile terminals. We also proposed a RHTML(Reduced HTML) to archive the adaptive tag reduction. Markup error correction process in the proposed adaptive document conversion mechanism converts a HTML(HyperText Markup Language) document into a XML(Extensible Markup Language) application document. This. process makes web document easy to handle with a DOM (Document Object Mode)) as the tree model and removes the hardware overhead in mobile terminals. Also, tag reduction process provides the adaptive web document with three DTD(Document Type Definition)s in the RHTML.

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.43-51
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• 2017

As the game industry is blooming, the generation of contents is far behind the consumption of contents. With this reason, it is necessary to afford the game contents considering level of game player's skill. In order to effectively solve this problem, Procedural Content Generation(PCG) using Artificial Intelligence(AI) is one of the plausible options. This paper proposes the procedural method to generate various monsters considering level of player's skill using genetic algorithm. One gene consists of the properties of a monster and one genome consists of genes for various monsters. A generated monster is evaluated by battle simulation with a player and then goes through selection and crossover steps. Using our proposed scheme, players adaptive monsters are generated procedurally based on genetic algorithm and the variety of monsters which are generated with different number of genome is compared.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2070-2086
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• 2014

As a kind of personal lifelog data, activity data have been considered as one of the most compelling information to understand the user's habits and to calibrate diagnoses. In this paper, we proposed a robust algorithm to sampling rates for human activity recognition, which identifies a user's activity using accelerations from a triaxial accelerometer in a smartphone. Although a high sampling rate is required for high accuracy, it is not desirable for actual smartphone usage, battery consumption, or storage occupancy. Activity recognitions with well-known algorithms, including MLP, C4.5, or SVM, suffer from a loss of accuracy when a sampling rate of accelerometers decreases. Thus, we start from particle swarm optimization (PSO), which has relatively better tolerance to declines in sampling rates, and we propose PSO with an adaptive boundary correction (ABC) approach. PSO with ABC is tolerant of various sampling rate in that it identifies all data by adjusting the classification boundaries of each activity. The experimental results show that PSO with ABC has better tolerance to changes of sampling rates of an accelerometer than PSO without ABC and other methods. In particular, PSO with ABC is 6%, 25%, and 35% better than PSO without ABC for sitting, standing, and walking, respectively, at a sampling period of 32 seconds. PSO with ABC is the only algorithm that guarantees at least 80% accuracy for every activity at a sampling period of smaller than or equal to 8 seconds.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.119-126
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• 2005

We propose a new content-based image retrieval using a representative color histogram and directional pattern histogram that is adaptive to the classification characteristics of the image blocks. In the proposed method the color and pattern feature vectors are extracted according to the characteristics o: the block classification after dividing the image into blocks with a fixed size. First, the divided blocks are classified as either luminance or color blocks depending on the saturation of the block. Thereafter, the color feature vectors are extracted by calculating histograms of the block average luminance co-occurrence for the luminance block and the block average colors for the color blocks. In addition, block directional pattern feature vectors are extracted by calculating histograms after performing the directional gradient classification of the luminance. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.166-175
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• 2020

Recently, application fields for processing and using digital image contents in various forms and types are rapidly increasing. Since image content is high value-added content, the intellectual property rights of this content must be protected in order to activate the production and use of the digital image content. In this paper, we propose a deep learning based watermark embedding and extraction network. The proposed method is to maximize the robustness of the watermark against malicious/non-malicious attacks while preserving the invisibility of the host image. This network consists of a preprocessing network that changes the watermark to have the same resolution as the host image, a watermark embedding network that embeds watermark data while maintaining the resolution of the host image by three-dimensionally concatenating the changed host image and the watermark information, and a watermark extraction network that reduces the resolution and extracts watermarks. This network verifies the invisibility and robustness of the proposed method by experimenting with various pixel value change attacks and geometric attacks against various watermark data and host images with various resolutions, and shows that this method is universal and practical.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.155-173
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• 2011

Recently, with the digitalization of a broadcasting system and the development of a communication technology, the existing trend of consuming media contents throughout the fixed-displayer and the dedicated channel is being changed. The existing user only could consume media contents under limited time and places because of the fixed-displayer and the dedicated channel. However, with advent of the IP-based terminals and HTTP adaptive streaming which transfer the media sequence according to the user's transmission condition, users become possible to enjoy the media content anytime anywhere. As the result of the alteration of the broadcasting surrounding, users can enjoy the media content while changing his terminals according to their preferences and circumstances. However, in case that users try to consume consecutively the content from last view-point ended in the previous terminal under current HTTP adaptive streaming environment, a user has to remember the last view-point, and then has to apply the view-point to the changed terminal. Thus, for solving this problem, this paper defines "User Profile" for describing the metadata for the chained content consume environment between the terminals. Also, for proving the proposed method, this paper try to demonstrate the proposed method throughout the realization of the system based on Smooth Streaming from Microsoft.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1178-1184
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• 1997

Encoding of segment contours is a critical part of a region-based coding system especially at low bit rates where the contour information occupies a majority of the bit rate. When approximating contours with polygons, a fixed upper bound on the distortion is set for the approximation process. Instead of using this fixed bound, adaptive approximation bound for a lossy coding of contourts is proposed in this paper. A function representing the relative importance of the contour segmentis defined to take into account the spatial content of the image. By using this function, the contour can be approximated adaptively. This allows a more general approach than the methods with the fixed distortion measure. The effectiveness of the adaptive contour coding approach is verified through experiments.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.251-253
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• 2005

In this paper, an adaptive algorithm is proposed in streaming MPEG-4 contents with fluctuating resource amount such as throughput of network conditions. MPEG-4 is the international standard for audiovisual presentation which is composed of object based media streams. The proposed technique provides the media stream corresponding an object with multiple media streams with different qualities and bit rate in order to support object based scalability to the MPEG-4 content. In addition, making the object streams adaptable, a feasible stream set selected from the multiple streams for transmission with optimal quality in the form of the current status.