• International Journal of Automotive Technology
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• 제6권1호
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• pp.53-63
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• 2005

We propose a fuzzy neural network (FNN) theory capable of deciding the quality of a road image prior to extracting lane-related information. The accuracy of lane-related information obtained by image processing depends on the quality of the raw images, which can be classified as good or bad according to how visible the lane marks on the images are. Enhancing the accuracy of the information by an image-processing algorithm is limited due to noise corruption which makes image processing difficult. The FNN, on the other hand, decides whether road images are good or bad with respect to the degree of noise corruption. A cumulative distribution function (CDF), a function of edge histogram, is utilized to extract input parameters from the FNN according to the fact that the shape of the CDF is deeply correlated to the road image quality. A suitability analysis shows that this deep correlation exists between the parameters and the image quality. The input pattern vector of the FNN consists of nine parameters in which eight parameters are from the CDF and one is from the intensity distribution of raw images. Experimental results showed that the proposed FNN system was quite successful. We carried out simulations with real images taken in various lighting and weather conditions, and obtained successful decision-making about $99\%$ of the time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.395-413
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• 2016

Image authentication is a technique aiming at protecting the integrity of digital images. Reversible image authentication has attracted much attention of researcher because it allows to authenticate tampered regions in the image and to reconstruct the stego image to its original version losslessly. In this paper, we propose a new, reversible image authentication scheme based on adaptive prediction error expansion (PEE) technique. In the proposed scheme, each image block is classified into smooth or complex regions. Then, according to the characteristic of each block, the authentication code is embedded adaptively to achieve high performance of tamper detection. The experimental results demonstrated that the proposed scheme achieves good quality of stego images. In addition, the proposed scheme has ability to reconstruct the stego image to its original version, if no modification is performed on it. Also demonstrated in the experimental results, the proposed scheme provides higher accuracy of tamper detection than state-of-the-art schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5170-5188
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• 2015

This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

• 한국정보처리학회논문지
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• 제7권4호
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• pp.1305-1315
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• 2000

It is known that a digital image enlargement technique can increase the size of he image but the practical enhancement of resolution is trifle because the frequency bandwidth of the original image is basically limited. To solve this problem, this paper proposes the digital image enlargement technique which interpolates the interpolation points of horizontal and vertical direction by weighting according to the direction of edge information with the component of FOI(First Order Interpolation)and output of the pseudomedian filter for image enlargement and interpolates the interpolation points of diagonal direction by selectively transposing the direction of the subwindows of the pseudomedian filter according to the distribution of neighbored pixels thereto in the extended image. According to the proposed methods, the digital image enlargement which preserves the characteristic of the pseudomedian filter capable of keeping the reconstruction of edge information and reflects the advantage of FOI can be performed. Therefore, visual artifacts could be effectively suppressed, and most characteristics and shape of the original image can be reconstructed as well.

• 통상정보연구
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• 제8권4호
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• pp.323-341
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• 2006

IThis research meets with empirical results in pursuit of aim as below mentioned. Firstly, it gets a line on two-way effects which have an effect on both (the country image and corporate image) by using the corporate image for the study of the country image. After making an analysis of the empirical test, found out that the corporate image has influence upon the country image significantly. Also found out that the country image has an effect on the corporate image powerfully. Therefore, it effects an inspection of evidence that the country image and corporate image have significantly positive concern, each other. Secondly, it is offering the way to use the culture marketing as grasping the mediating effects, which culture difference has influence upon the country image and the corporate image. The mediating effects show that the country image has influence on the corporate image more as culture difference is bigger.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5963-5980
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• 2017

Image scrambling is an important technology in information hiding, where the Arnold transformation is widely used. Several researchers have proposed the application of $H{\acute{e}}non$ map in square image scrambling, and certain improved technologies require scrambling many times to achieve a good effect without resisting chosen-plaintext attack although it can be directly applied to non-square images. This paper presents a non-square image scrambling algorithm, which can resist chosen-plaintext attack based on a chaotic two-dimensional Sine Logistic modulation map and $H{\acute{e}}non$ map (2D-SLHM). Theoretical analysis and experimental results show that the proposed algorithm has advantages in terms of key space, efficiency, scrambling degree, ability of anti-attack and robustness to noise interference.

• 전자공학회논문지CI
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• 제48권3호
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• pp.91-101
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• 2011

정보통신 기술의 급격한 발전으로 인해 인터넷이 대중화됨에 따라 인터넷을 이용한 사이버 공간상에 정보의 상호교환, 전자 상거래, 인터넷뱅킹 등의 사회 활동이 활발해지고 있다. 하지만, 인터넷 사용의 편리함을 추구하는 경향에 의해 개인식별용 증명서(주민등록증, 운전면허증, 여권, 학생증 등)들이 전자적인 매체로 표현되어 인터넷상에서 노출되는 경우가 빈번하게 발생하고 있다. 따라서 본 연구에서는 인터넷상에 노출된 개인정보가 포함된 이미지들을 효율적으로 검색하기 위한 방안을 제안한다. 제안한 방안은 이미지의 색상과 질감, 그리고 모양 특징정보들 중에서 개인식별정보가 포함된 이미지들에서 고유한 특징정보들을 분석하여 추출한 후 이를 이용하여 개인식별정보가 포함된 이미지들을 검색한다. 제안한 방안을 실험한 결과, 전체 개인 식별정보가 포함된 이미지들 중에서 약 89%이상의 검색 성공률과 이미지 파일 당 수행시간은 약 0.17초가 소모되었다. 이러한 결과를 바탕으로 실제 인터넷상에서 개인식별정보가 포함된 이미지 파일들의 검색과 노출 여부 판단을 위한 시스템에 효과적으로 적용할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3823-3840
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• 2020

Recently, auto-encoder has emerged as the most popular method in convolutional neural network (CNN) based image compression and has achieved impressive performance. In the traditional auto-encoder based image compression model, the encoder simply sends the features of last layer to the decoder, which cannot allocate bits over different spatial regions in an efficient way. Besides, these methods do not fully exploit the contextual information under different receptive fields for better reconstruction performance. In this paper, to solve these issues, a novel auto-encoder model is designed for image compression, which can effectively transmit the hierarchical features of the encoder to the decoder. Specifically, we first propose an adaptive bit-allocation strategy, which can adaptively select an importance channel. Then, we conduct the multiply operation on the generated importance mask and the features of the last layer in our proposed encoder to achieve efficient bit allocation. Moreover, we present an additional novel perceptual loss function for more accurate image details. Extensive experiments demonstrated that the proposed model can achieve significant superiority compared with JPEG and JPEG2000 both in both subjective and objective quality. Besides, our model shows better performance than the state-of-the-art convolutional neural network (CNN)-based image compression methods in terms of PSNR.

• Journal of Information Processing Systems
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• 제14권5호
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• pp.1150-1166
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• 2018

This paper presents a physical storage design method for image access structures using transformation techniques of multidimensional file organizations in image information systems. Physical storage design is the process of determining the access structures to provide optimal query processing performance for a given set of queries. So far, there has been no such attempt in the image information system. We first show that the number of pages to be accessed decreases as the shape of the given retrieval query region and that of the data page region become similar in the transformed domain space. Using these properties, we propose a method for finding an optimal image access structure by controlling the shapes of the page regions. For the performance evaluation, we have performed many experiments with a multidimensional file organization using transformation techniques. The results indicate that our proposed method is at least one to maximum five times faster than the conventional method according to the query pattern within the scope of the experiments. The result confirms that the proposed physical storage design method is useful in a practical way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권5호
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• pp.910-924
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• 2010

As Internet usage has increased, the risk of adolescents being exposed to adult content and harmful information on the Internet has also risen. To help prevent adolescents accessing this content, a novel detection method for adult images is proposed. The proposed method involves three steps. First, the Image Of Interest (IOI) is extracted from the image background. Second, the IOI is distinguished from the segmented image using a novel weighting mask, and it is determined to be acceptable or unacceptable. Finally, the features (color and texture) of the IOI or original image are compared to a critical value; if they exceed that value then the image is deemed to be an adult image. A Receiver Operating Characteristic (ROC) curve analysis was performed to define this optimal critical value. And, the textural features are identified using a gray level co-occurrence matrix. The proposed method increased the precision level of detection by applying a novel weighting mask and a receiver operating characteristic curve. To demonstrate the effectiveness of the proposed method, 2850 adult and non-adult images were used for experimentation.