• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.157-160
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• 2003

Recently, several steganographic algorithms for two-color binary images have been proposed. In this paper, we propose a steganographic algorithm which embeds a secret message into bitmap images and palette-based images. To embed a message, the suggested algorithm divides a bitmap image into bit-plane images from LSB-plane to MSB-plane for each pixel, and considers each bit-plane image as a binary one. The algorithm splits each bit-plane image into m$\times$n blocks. and embeds a r-bit(r=[log$_2$(mn+1]-1) message into the block. And our schemes embed a message to every bit-plane from LSB to MSB to maximize the amount of embedded message and to minimize the degradation. The schemes change at most two pixels in each block. Therefore, the maximal color changes of the new algorithm are much smaller than other bit-plane embedding schemes' such as the substantial substitution schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.658-665
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• 2005

Re-assignment scheme of index in index image is called reindexing. It has been well known that index image can be reindexed without losslessness. In this paper, we introduces an adaptive rank based reindexing scheme using co-occurrence frequency between neighboring pixels. Original index image can be converted into rank image by the proposed scheme. Using the proposed scheme, a better compression efficiency can be expected because most of the reindexed values(rank) get distributed with a smaller variance than the original index image. Experinental results show that the proposed scheme achieves a much better compression performance over GIF, arithmetic coding, Zeng's algorithm and RIAC scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4788-4813
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• 2019

In this paper, we introduce concepts of optimal and near optimal secret data hiding schemes. We present a new digital image steganography approach based on the Galois field $GF(p^m)$ using graph and automata to design the data hiding scheme of the general form ($k,N,{\lfloor}{\log}_2p^{mn}{\rfloor}$) for binary, gray and palette images with the given assumptions, where k, m, n, N are positive integers and p is prime, show the sufficient conditions for the existence and prove the existence of some optimal and near optimal secret data hiding schemes. These results are derived from the concept of the maximal secret data ratio of embedded bits, the module approach and the fastest optimal parity assignment method proposed by Huy et al. in 2011 and 2013. An application of the schemes to the process of hiding a finite sequence of secret data in an image is also considered. Security analyses and experimental results confirm that our approach can create steganographic schemes which achieve high efficiency in embedding capacity, visual quality, speed as well as security, which are key properties of steganography.

• Journal of IKEEE
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• v.28 no.3
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• pp.352-359
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• 2024

This paper proposes a CNN-ViT hybrid model that automatically evaluates the aesthetic quality of images by combining local and global features. In this approach, CNN is used to extract local features such as color and object placement, while ViT is employed to analyze the aesthetic value of the image by reflecting global features. Color composition is derived by extracting the primary colors from the input image, creating a color palette, and then passing it through the CNN. The Rule of Thirds is quantified by calculating how closely objects in the image are positioned near the thirds intersection points. These values provide the model with critical information about the color balance and spatial harmony of the image. The model then analyzes the relationship between these factors to predict scores that align closely with human judgment. Experimental results on the AADB image database show that the proposed model achieved a Spearman's Rank Correlation Coefficient (SRCC) of 0.716, indicating more consistent rank predictions, and a Pearson Correlation Coefficient (LCC) of 0.72, which is 2~4% higher than existing models.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.143-151
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• 2021

The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.21-26
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• 2004

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. The basic problem is how to display 256 colors or less colors, called color palette, In this paper, we propose improved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on the responsibility of human visual system according to changes of three Primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective quality test and WSNR.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1950-1962
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• 2008

Today the importance of color image is increasing for the brands as well as the products. This study was performed to classily the color image of baby's wear brands and to suggest how the color is effectively planned for the image. In order to classify the color image of 7 baby's wear brands, color palettes of 7 brands were also made by 6 subgroups, each season(summer, fall) by gender(boy, girl, new-born) and based on manufactured garments which were collected by on-line shops. Questionaries were organized with 40 pieces of the color palettes prints for 6 subgroups by 7 brands and 20 baby's wear image adjectives. The total 320 copies were used in the survey to students majored in fashion design. Questionaries were analyzed by factor analysis from SPSS 12.0 package program. There are 4 main factors for the color images of baby's wear brands, 'liveliness', 'loveliness', 'chic', 'neatness'. Not hue, but tone is more important to express the characteristics of color images of baby's wear brands. Also white and black are importantly used for baby's wear. The consistency of the brand color image across gender and season is very important to identify and strengthen the color image of brand.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.4
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• pp.112-128
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• 2015

To consider an identity about traditional folk village, this study analyzes color characteristic of traditional folk village by targeting Cuandixia folk village in China. For method of study, color is analyzed by KSCA(Korea Standard Color Analysis) program and images of color are drawn by I.R.I. Based on these, four results are came out. First, color distribution of Cuandixia is appeared in YR, R, Y, GY order. Furthermore, there are no affiliation of BG, and B but a lot of affiliation of YR. Second, the whole is made up of color that is applied to mist gray/low chroma in the value and chroma stakes. Especially, high chroma is extracted by only commercial old house, the rest is made up of middle and low chroma color. Third, dark color is the most by KS Color System and dark reddish gray and medium gray are occupied most part. Fourth, the whole atmosphere of village is static and hard, and the image is researched as gentle. Through the research, It applies extracted color palette for plan and preservation of traditional folk village. As using the color that is reflected in national and local distinct characteristic, preserving the color reflected in history and culture of the village, and applying color planning considered harmony with surrounding environment, it is expected that it can help to direct the color involved traditional and cultural meaning.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.