Готові списки джерел за темами / COLOR IMAGE STEGANOGRAPHY

Добірка наукової літератури з теми "COLOR IMAGE STEGANOGRAPHY"

Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "COLOR IMAGE STEGANOGRAPHY"

1

Xu, Meng, Xiangyang Luo, Jinwei Wang, and Hao Wang. "Color image steganalysis based on quaternion discrete cosine transform." Electronic Research Archive 31, no. 7 (2023): 4102–18. http://dx.doi.org/10.3934/era.2023209.

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Анотація:
<abstract> <p>With the rapid development and application of Internet technology in recent years, the issue of information security has received more and more attention. Digital steganography is used as a means of secure communication to hide information by modifying the carrier. However, steganography can also be used for illegal acts, so it is of great significance to study steganalysis techniques. The steganalysis technology can be used to solve the illegal steganography problem of computer vision and engineering applications technology. Most of the images in the Internet are color images, and steganalysis for color images is a very critical problem in the field of steganalysis at this stage. Currently proposed algorithms for steganalysis of color images mainly rely on the manual design of steganographic features, and the steganographic features do not fully consider the internal connection between the three channels of color images. In recent years, advanced steganography techniques for color images have been proposed, which brings more serious challenges to color image steganalysis. Quaternions are a good tool to represent color images, and the transformation of quaternions can fully exploit the correlation among color image channels. In this paper, we propose a color image steganalysis algorithm based on quaternion discrete cosine transform, firstly, the image is represented by quaternion, then the quaternion discrete cosine transform is applied to it, and the coefficients obtained from the transformation are extracted to design features of the coeval matrix. The experimental results show that the proposed algorithm works better than the typical color image steganalysis algorithm.</p> </abstract>
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2

Sundos A. Hameed Al-azawi and Abbas A. AbulHameed. "Information Hiding in Color Image Using Steganographic technique." Journal of the College of Basic Education 17, no. 70 (December 22, 2022): 113–22. http://dx.doi.org/10.35950/cbej.vi.8480.

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Анотація:
Steganography is one of the important research subjects in the field of information security. It enables secret communication by embedding messages in the texts, images, audio, video files or other digital carriers. Among all the image information hiding methods, LSB embedding is widely used for its high hiding capacity and it is with great significance to detect the images with hidden messages produced by LSB embedding effectively, accurately and reliably. Therefore, many experts made efforts on the LSB steganography and steganalysis research over the years. This research presents a steganographic technique based on using LSB of one of the pixel color components in the image and changes them according to the message’s bits to hide. The rest of bits in the pixel color component selected are also changed in order get the nearest color to the original one in the scale of colors. This new method has been tested with others that work in the spatial domain through applying some common metrics which give us good result as a compared with the other steganographic tools.
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3

Alwan, Zena Ahmed, Hamid Mohammed Farhan, and Siraj Qays Mahdi. "Color image steganography in YCbCr space." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (February 1, 2020): 202. http://dx.doi.org/10.11591/ijece.v10i1.pp202-209.

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Анотація:
Steganography is a best method for in secret communicating information during the transference of data. Images are an appropriate method that used in steganography can be used to protection the simple bits and pieces. Several systems, this one as color scale images steganography and grayscale images steganography, are used on color and store data in different techniques. These color images can have very big amounts of secret data, by using three main color modules. The different color modules, such as HSV-(hue, saturation, and value), RGB-(red, green, and blue), YCbCr-(luminance and chrominance), YUV, YIQ, etc. This paper uses unusual module to hide data: an adaptive procedure that can increase security ranks when hiding a top secret binary image in a RGB color image, which we implement the steganography in the YCbCr module space. We performed Exclusive-OR (XOR) procedures between the binary image and the RGB color image in the YCBCR module space. The converted byte stored in the 8-bit LSB is not the actual bytes; relatively, it is obtained by translation to another module space and applies the XOR procedure. This technique is practical to different groups of images. Moreover, we see that the adaptive technique ensures good results as the peak signal to noise ratio (PSNR) and stands for mean square error (MSE) are good. When the technique is compared with our previous works and other existing techniques, it is shown to be the best in both error and message capability. This technique is easy to model and simple to use and provides perfect security with unauthorized.
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4

Mohammed Zaki, Hassan. "Color Pattern Steganography in Images." Technium: Romanian Journal of Applied Sciences and Technology 9 (April 21, 2023): 60–65. http://dx.doi.org/10.47577/technium.v9i.8337.

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Анотація:
Text steganography into images is one of the important strategies that are used to hide the transmitted secret messages via internet connections. Most of the proposed methods required mapping key to recover the hidden secret messages and implement more complex algorithms in hiding and recovering processes. The paper proposed an improved method to hide text in image cove based on the color pattern of the cover image. It based on the sequence of the new occurrence of the color. The results showed that the proposed method has high performance in hiding with extremely low PSNR(<0.002). The low differences between the original image and the stegno image provide more secured hiding that satisfied the State-of-Art. The proposed method can be used in transmitting classified and confidential messages via public internet connections.
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5

Zhang, Shanqing, Shengqi Su, Li Li, Qili Zhou, Jianfeng Lu, and Chin-Chen Chang. "An Image Style Transfer Network Using Multilevel Noise Encoding and Its Application in Coverless Steganography." Symmetry 11, no. 9 (September 11, 2019): 1152. http://dx.doi.org/10.3390/sym11091152.

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Анотація:
Most of the existing image steganographic approaches embed the secret information imperceptibly into a cover image by slightly modifying its content. However, the modification traces will cause some distortion in the stego-image, especially when embedding color image data that usually contain thousands of bits, which makes successful steganalysis possible. A coverless steganographic approach without any modification for transmitting secret color image is proposed. We propose a diversity image style transfer network using multilevel noise encoding. The network consists of a generator and a loss network. A multilevel noise to encode matching the subsequent convolutional neural network scale is used in the generator. The diversity loss is increased in the loss network so that the network can generate diverse image style transfer results. Residual learning is introduced so that the training speed of network is significantly improved. Experiments show that the network can generate stable results with uniform texture distribution in a short period of time. These image style transfer results can be integrated into our coverless steganography scheme. The performance of our steganography scheme is good in steganographic capacity, anti-steganalysis, security, and robustness.
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6

Eyssa, Asmaa Abdelmonem, Fathi Elsaid Abdelsamie, and Abdelaziz Elsaid Abdelnaiem. "An Efficient Image Steganography Approach over Wireless Communication System." Wireless Personal Communications 110, no. 1 (September 21, 2019): 321–37. http://dx.doi.org/10.1007/s11277-019-06730-2.

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Анотація:
Abstract This paper presents a robust color image steganography approach for image communication over wireless communication systems. The objective of this approach is to hide three color images in one color cover image to increase the capacity of hiding as most previously published steganography approaches suffer from a capacity problem. Moreover, the investigation of wireless communication of steganography images is presented in this paper to study the sensitivity of extraction of hidden images to the channel degradation effects, which is not studied appropriately in the literature. The proposed approach depends on the Discrete Cosine and Discrete Wavelet transform. The cover image is first transformed to luminance and chrominance components for embedding the images to be hidden. The secret images are encrypted by chaotic Baker map, which is a good representative of the family of permutation-based algorithms, which tolerate the channel degradations better. The investigated wireless communication system is the Orthogonal Frequency Division Multiplexing system with channel equalization. The simulation results reveal the success of the proposed work for robust image communication.
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7

PourArian, Mohammad Rasoul, and Ali Hanani. "Blind Steganography in Color Images by Double Wavelet Transform and Improved Arnold Transform." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 3 (September 1, 2016): 586. http://dx.doi.org/10.11591/ijeecs.v3.i3.pp586-600.

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Анотація:
<p>Steganography is a method which can put data into a media without a tangible impact on the cover media. In addition, the hidden data can be extracted with minimal differences. In this paper, two-dimensional discrete wavelet transform is used for steganography in 24-bit color images. This steganography is of blind type that has no need for original images to extract the secret image. In this algorithm, by the help of a structural similarity (SSIM) and a two-dimensional correlation coefficient, it is tried to select part of sub-band cover image instead of embedding location. These sub-bands are obtained by 3-levels of applying the DWT. Also to increase the steganography resistance against cropping or insert visible watermark, two channels of color image is used simultaneously. In order to raise the security, an encryption algorithm based on Arnold transform was also added to the steganography operation. </p>
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8

Shao, Guoqiang, Longmei Jie, and Dan Shen. "A Novel Steganography Scheme for Color Image Based on HLS Translation." Journal of Physics: Conference Series 2025, no. 1 (September 1, 2021): 012058. http://dx.doi.org/10.1088/1742-6596/2025/1/012058.

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Анотація:
Abstract In recent years, steganography has attracted extensive attention, but most of steganography schemes are aimed at grayscale images. Therefore, a novel steganography scheme for color image based on HLS translation is proposed in this paper. Firstly, the color cover image is decomposed from RGB three channels to HLS three channels. Then the image of H channel is selected as the cover image for embedding secret information due to its texture feature of original image. The universal distortion function UNIWARD is utilized to embed the secret information into the image of H channel. Finally, the steg image transmitted in common channel is obtained by inverse HLS transform using the single channel image embedding the secret information. The extensive experimental results indicate that our scheme has high security and can also resist the detection of steganalysis schemes based on CNN.
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9

Xiao, Hong, and Panchi Li. "Quantum steganography based on reflected gray code for color images." Intelligent Decision Technologies 14, no. 3 (September 29, 2020): 291–312. http://dx.doi.org/10.3233/idt-190034.

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Анотація:
Digital steganography is the art and science of hiding information in covert channels, so as to conceal the information and prevent the detection of hidden messages. On the classic computer, the principle and method of digital steganography has been widely and deeply studied, and has been initially extended to the field of quantum computing. Quantum image steganography is a relatively active branch of quantum image processing, and the main strategy currently used is to modify the LSB of the cover image pixels. For the existing LSB-based quantum image steganography schemes, the embedding capacity is no more than 3 bits per pixel. Therefore, it is meaningful to study how to improve the embedding capacity of quantum image steganography. This work presents a novel steganography using reflected Gray code for color quantum images, and the embedding capacity of this scheme is up to 6 bits per pixel. In proposed scheme, the secret qubit sequence is considered as a sequence of 6-bit segments. For 6 bits in each segment, the first 3 bits are embedded into the second LSB of RGB channels of the cover image, and the remaining 3 bits are embedded into the LSB of RGB channels of the cover image using reflected-Gray code to determine the embedded bit from secret information. Following the transforming rule, the LSBs of stego-image are not always same as the secret bits and the differences are up to almost 50%. Experimental results confirm that the proposed scheme shows good performance and outperforms the previous ones currently found in the literature in terms of embedding capacity.
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10

Hutapea, Destri Yanti, and Octaviani Hutapea. "WATERMARKING METHOD OF REMOTE SENSING DATA USING STEGANOGRAPHY TECHNIQUE BASED ON LEAST SIGNIFICANT BIT HIDING." International Journal of Remote Sensing and Earth Sciences (IJReSES) 15, no. 1 (July 6, 2018): 63. http://dx.doi.org/10.30536/j.ijreses.2018.v15.a2824.

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Анотація:
Remote sensing satellite imagery is currently needed to support the needs of information in various fields. Distribution of remote sensing data to users is done through electronic media. Therefore, it is necessary to make security and identity on remote sensing satellite images so that its function is not misused. This paper describes a method of adding confidential information to medium resolution remote sensing satellite images to identify the image using steganography technique. Steganography with the Least Significant Bit (LSB) method is chosen because the insertion of confidential information on the image is performed on the rightmost bits in each byte of data, where the rightmost bit has the smallest value. The experiment was performed on three Landsat 8 images with different area on each composite band 4,3,2 (true color) and 6,5,3 (false color). Visually the data that has been inserted information does not change with the original data. Visually, the image that has been inserted with confidential information (or stego image) is the same as the original image. Both images cannot be distinguished on histogram analysis. The Mean Squared Error value of stego images of all three data less than 0.053 compared with the original image. This means that information security with steganographic techniques using the ideal LSB method is used on remote sensing satellite imagery.
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Більше джерел

Дисертації з теми "COLOR IMAGE STEGANOGRAPHY"

1

Abdulrahman, Hasan. "Oriented filters for feature extraction in digital Images : Application to corners detection, Contours evaluation and color Steganalysis." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTS077/document.

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Анотація:
L’interprétation du contenu de l’image est un objectif très important dans le traitement de l’image et la vision par ordinateur. Par conséquent, plusieurs chercheurs y sont intéressés. Une image contient des informations multiples qui peuvent être étudiés, telles que la couleur, les formes, les arêtes, les angles, la taille et l’orientation. En outre, les contours contiennent les structures les plus importantes de l’image. Afin d’extraire les caractéristiques du contour d’un objet, nous devons détecter les bords de cet objet. La détection de bords est un point clé dans plusieurs applications, telles que :la restauration, l’amélioration de l’image, la stéganographie, le filigrane, la récupération, la reconnaissance et la compression de l’image, etc. Toutefois, l’évaluation de la performance de la méthode de détection de bords reste un grand défi. Les images numériques sont parfois modifiées par une procédure légale ou illégale afin d’envoyer des données secrètes ou spéciales. Afin d’être moins visibles, la plupart des méthodes stéganographiques modifient les valeurs de pixels dans les bords/textures de parties de l’image. Par conséquent, il est important de détecter la présence de données cachées dans les images numériques. Cette thèse est divisée principalement en deux parties.La première partie discute l’évaluation des méthodes de détection des bords du filtrage, des contours et des angles. En effet, cinq contributions sont présentées dans cette partie : d’abord, nous avons proposé un nouveau plan de surveillance normalisée de mesure de la qualité. En second lieu, nous avons proposé une nouvelle technique pour évaluer les méthodes de détection des bords de filtrage impliquant le score minimal des mesures considérées. En plus, nous avons construit une nouvelle vérité terrain de la carte de bords étiquetée d’une manière semi-automatique pour des images réelles.En troisième lieu, nous avons proposé une nouvelle mesure prenant en compte les distances de faux points positifs pour évaluer un détecteur de bords d’une manière objective. Enfin, nous avons proposé une nouvelle approche de détection de bords qui combine la dérivée directionnelle et l’homogénéité des grains. Notre approche proposée est plus stable et robuste au bruit que dix autres méthodes célèbres de détection. La seconde partie discute la stéganalyse de l’image en couleurs, basée sur l’apprentissage automatique (machine learning). En effet, trois contributions sont présentées dans cette partie : d’abord, nous avons proposé une nouvelle méthode de stéganalyse de l’image en couleurs, basée sur l’extraction de caractéristiques de couleurs à partir de corrélations entre les gradients de canaux rouge, vert et bleu. En fait, ces caractéristiques donnent le cosinus des angles entre les gradients. En second lieu, nous avons proposé une nouvelle méthode de stéganalyse de l’image en couleurs, basée sur des mesures géométriques obtenues par le sinus et le cosinus des angles de gradients entre tous les canaux de couleurs. Enfin, nous avons proposé une nouvelle méthode de stéganalyse de l’image en couleurs, basée sur une banque de filtres gaussiens orientables. Toutes les trois méthodes proposées présentent des résultats intéressants et prometteur en devançant l’état de l’art de la stéganalyse en couleurs
Interpretation of image contents is very important objective in image processing and computer vision. Wherefore, it has received much attention of researchers. An image contains a lot of information which can be studied such as color, shapes, edges, corners, size, and orientation. Moreover, contours include the most important structures in the image. In order to extract features contour of an object, we must detect the edges of that object. Edge detection results, remains a key point and very important step in wide range of applications such as: image restoration, enhancement, steganography, watermarking, image retrieval, recognition, compression, and etc. An efficient boundary detection method should create a contour image containing edges at their correct locations with a minimum of misclassified pixels. However, the performance evaluationof the edge detection results is still a challenging problem. The digital images are sometimes modify by a legal or illegal data in order to send special or secret data. These changes modify slight coefficient values of the image. In order to be less visible, most of the steganography methods modify the pixel values in the edge/texture image areas. Therefore, it is important to detect the presence of hidden data in digital images. This thesis is divided mainly into two main parts. The first part, deals with filtering edge detection, contours evaluation and corners detection methods. More deeply, there are five contributions are presented in this part: first, proposed a new normalized supervised edge map quality measure. The strategy to normalize the evaluation enables to consider a score close to 0 as a good edge map, whereas a score 1 translates a poor segmentation. Second, proposed a new technique to evaluate filtering edge detection methods involving the minimum score of the considerate measures. Moreover, build a new ground truth edge map labelled in semi-automatic way in real images. Third, proposed a new measure takes into account the distances of false positive points to evaluate an edge detector in an objective way. Finally, proposed a new approach for corner detection based on the combination of directional derivative and homogeneity kernels. The proposed approach remains more stable and robust to noise than ten famous corner detection methods. The second part, deals with color image steganalysis, based on a machine learning classification. More deeply, there are three contributionsare presented in this part: first, proposed a new color image steganalysis method based on extract color features from correlations between the gradients of red, green and blue channels. Since these features give the cosine of angles between gradients. Second, proposed a new color steganalysis method based on geometric measures obtained by the sine and cosine of gradient angles between all the color channels. Finally, proposed a new approach for color image steganalysisbased on steerable Gaussian filters Bank.All the three proposed methods in this part, provide interesting and promising results by outperforming the state-of-art color image steganalysis
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2

Tseng, Hsin-Chun, and 曾信淳. "A Study on Adaptive Steganography-based Optical Color Image Cryptosystem." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/95881906324364679106.

Повний текст джерела
Анотація:
碩士
亞洲大學
資訊工程學系碩士班
98
In this thesis, an optical color image cryptosystem with a color image and data hiding scheme is proposed. In the proposed optical cryptosystem, a secret color image is embedded into host image of the same size to become a stego-image. The secret color image is hidden in the phase term of the host image. Then the stego-image is encrypted by the optical cryptosystem which employs a double random phase encoding algorithm. During the encoding process, secret data is embedded into the encrypted image by an adaptive steganographic technique. The secret image and data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. In comparison with the traditional hiding scheme, a high data embedding capacity and high visual quality of the decrypted host and secret images are achieved. Experimental results show that the proposed image and data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
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3

Lin, Hung-Jen, and 林泓任. "True Color Image Steganography Using Palette and Minimum Spanning Tree." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/82039255082858476168.

Повний текст джерела
Анотація:
碩士
大葉大學
資訊工程學系碩士班
94
Steganography is a application of data hiding, the main point is that increases the security and camouflage by hiding secret message into digital media to send to other person. Some methods and literatures get stego image after embedding secret message by using a color set which had be created by clustering and quantification. The other people can get secret message by using the color set, which is the same with sender, and some procedures after receiving the stego image. But the color set usually limits the quality of stego image, and there is difference about the type and accuracy of color set by using the different of methods about clustering and quantification, it has influence on stego image. This paper aimed this defect and proposed a new method to reduce the influence, caused by color set, on stego image. Our main target is true color image, it usually be reduced the number of colors by the color set in some traditional methods, the influence is very serious. The stego image created by our method do not be reduced the number of colors by the color set, so the type of it is the same with original image. The structure of embedding secret message is decided by minimum spanning tree. In the final we propose the result by experiment and comparing with other methods to show the improvement of our method.
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4

kanagi, Karamo, and 卡拉莫. "Steganography by Color Images Using Advanced Encryption Standard (AES)." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/72471940294150032343.

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Анотація:
碩士
國立清華大學
資訊系統與應用研究所
103
資訊安全近期在資料通訊中佔有很大的重要議題。其中，影像藏密及密碼學都是確保祕密訊息的方法。影像藏密是把一張訊息藏在數位媒體並且遮掩一些資訊。但是如果分開使用這些技術，並沒有辦法完整的保護資訊安全。為了要保護資訊安全及機密資訊，我們必須結合影像藏密及密碼學去提供更強大的資訊通訊來防止入侵者。 在這篇論文中，我們提供一個影像藏密的方法去專注在24位元的彩色影像。這項方法使用了標籤圖像文件格式，並且在使用最低有效位（LSB）方法的圖像嵌入裡面，使用AES 128位元的加密算法的秘密信息進行加密，透過減少到封面圖像所做的更改量來提高LSB的方法。在這項實驗中，比較分析了通過計算均方誤差（MSE）和峰值信噪比（PSNR）證明了該方法的有效性。最後的結果顯示此方法能保持圖像質量和安全的更高的水平。
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5

Lin, Kai-Chun, and 林凱鈞. "The Study of Steganographic Scheme with Tolerating Losing Compression Process for Color Image." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/56344319046873135894.

Повний текст джерела
Анотація:
碩士
淡江大學
資訊工程學系碩士班
93
In this paper, we present a new steganographic scheme used to embed secret text data into color images. Not only preserve the visual quality, we can use JPEG to com-press the stego-image. JPEG is the most common used image compression technique which reduces the image size drastically without losing the image quality seriously. There are many steganographic scheme have been proposed, but most of them can’t tolerate JPEG compression. That is, after JPEG compressing, the hidden data will be damaged critically. If the embedding data are pictures, accuracy losing would be ac-cepted. But for text data embedding approaches, even one bit error will lead the ex-tracted data to be totally useless. In our scheme, the hidden data are encoded by error correction technique first. Then we embed the encoded data in the spatial domain di-rectly by adjusting the pixel relation in each 3×3 image block. We also adopt the concept of error diffusion method used in halftone technique to improve the image quality to human visual system. By this way, the extracted data from a compressed stego-image could be completely correct.
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6

Tseng, Chiung-Chen, and 曾瓊蓁. "A High Payload Steganography Scheme for Color Images Based on BTC and Hybrid Strategy." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/03826317414928902865.

Повний текст джерела
Анотація:
碩士
亞洲大學
資訊工程學系
103
With advances in computer networks and applications, the Internet has become indispensable to delivering confidential data. Information security is a prime concern as people’s use of the Internet increases. Various research studies have been done to better protect data in transit and ensure information security. Cryptographic methods and steganography are the most commonly used strategies to secure communications on the Internet. To compliment cryptographic methods, which do not hide secret data in transmitted packets, steganography is used to embed secret data so that unintended recipients are unaware of the secret data been transmitted in a steganographic image. Therefore, the quality of the stego image must be high for the embedded secret message. In general, information hiding (also called data hiding or data embedding) technique includes digital watermarking and steganography. These information hiding methods are currently used by many researchers for various applications. Embedding capacity is one of the key issues in data hiding research. In theory, a higher embedding capacity in the original medium usually means poorer visual quality. Block Truncation Coding (BTC) is one of the popular compression techniques used in image data hiding because of its low computation cost and ease of implementation. For a color image, there are three pairs of high mean and low mean values with three bitmaps. A common bitmap can be used to reduce the size of the BTC compression code. Chang et al. presented a data hiding method to conceal secret data in the color image BTC compression code by rearranging the encoding sequences of the high mean and low mean values. The proposed method attempts to embed more secret data into the color BTC compression code. In this thesis, a novel method is proposed to encrypt data based on the number of the element ‘1’. If the number is even, the data for the secret bit is ‘0’; otherwise, the secret bit is ‘1’. Furthermore, the Less Significant Bit (LSB) of all high mean and low mean pairs can also be used to embed the secret data. Experimental results show that with the proposed method, each block conceals at least 10 secret bits while good visual quality is maintained.
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Частини книг з теми "COLOR IMAGE STEGANOGRAPHY"

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Singla, Deepali, and Mamta Juneja. "Hybrid Edge Detection-Based Image Steganography Technique for Color Images." In Advances in Intelligent Systems and Computing, 277–80. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2009-1_32.

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Goswami, Anirban, Dipankar Pal, and Nabin Ghoshal. "Two Stage Color Image Steganography Using DCT (TSCIS-DCT)." In Advances in Intelligent Systems and Computing, 755–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35314-7_86.

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Zeng, Cheng, Jingbing Li, Jingjun Zhou, and Saqib Ali Nawaz. "Color Image Steganography Scheme Based on Convolutional Neural Network." In Advances in Artificial Intelligence and Security, 265–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78621-2_21.

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Hu, Yu-Chen, Chin-Feng Lee, and Yi-Hung Liu. "Reversible Image Steganography for Color Image Quantization Based on Lossless Index Coding." In Security with Intelligent Computing and Big-data Services, 185–95. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76451-1_18.

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Sharma, Annu, Kalpana Sharma, and Amit Kr Chaturvedi. "Proposing a Novel Scheme for Improving LSB Image Steganography with Color Image." In Proceedings of International Conference on Communication and Artificial Intelligence, 399–407. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0976-4_33.

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Khashandarag, Asghar Shahrzad, Ahmad Habibizad Navin, Mir Kamal Mirnia, and Hamid Haji Agha Mohammadi. "An Optimized Color Image Steganography Using LFSR and DFT Techniques." In Advanced Research on Computer Education, Simulation and Modeling, 247–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21802-6_40.

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Shet, K. Sathish, Nagaveni, and A. R. Aswath. "Image Steganography Using Integer Wavelet Transform Based on Color Space Approach." In Advances in Intelligent Systems and Computing, 839–48. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11933-5_95.

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Inan, Yucel. "Quality Metrics of LSB Image Steganography Technique for Color Space HSI." In 11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021, 67–74. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92127-9_13.

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Li, Ya-Lin, and Wen-Hsiang Tsai. "New Image Steganography via Secret-Fragment-Visible Mosaic Images by Nearly-Reversible Color Transformation." In Advances in Visual Computing, 64–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24031-7_7.

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Nolkha, Avneesh, Sunil Kumar, and V. S. Dhaka. "Image Steganography Using LSB Substitution: A Comparative Analysis on Different Color Models." In Smart Systems and IoT: Innovations in Computing, 711–18. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8406-6_67.

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Тези доповідей конференцій з теми "COLOR IMAGE STEGANOGRAPHY"

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Ahuja, Sarthak, C. Udaya Kumar, and S. Hemalatha. "Competitive Coevolution for Color Image Steganography." In 2019 International Conference on Intelligent Computing and Control Systems (ICCS). IEEE, 2019. http://dx.doi.org/10.1109/iccs45141.2019.9065844.

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Yang, Ching-Yu. "Color Image Steganography Based on Module Substitutions." In Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/iihmsp.2007.4457667.

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Hemalatha, R. K., and Patra Maneesha. "Unified embedding method for color image steganography." In 2016 International Conference on Information Communication and Embedded Systems (ICICES). IEEE, 2016. http://dx.doi.org/10.1109/icices.2016.7518872.

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Chuang, Cheng-Hung, and Guo-Shiang Lin. "Adaptive steganography-based optical color image cryptosystems." In 2009 IEEE International Symposium on Circuits and Systems - ISCAS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iscas.2009.5118094.

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Jani Anbarasi, L., and S. Kannan. "Secured secret color image sharing with steganography." In 2012 International Conference on Recent Trends in Information Technology (ICRTIT). IEEE, 2012. http://dx.doi.org/10.1109/icrtit.2012.6206748.

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Anurag and Shweta Meena. "Color Image Steganography Using Random Key Matrix." In 2018 3rd International Conference for Convergence in Technology (I2CT). IEEE, 2018. http://dx.doi.org/10.1109/i2ct.2018.8529425.

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kumar, Deepak. "Hiding Text In Color Image Using YCbCr Color Model: An Image Steganography approach." In 2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT). IEEE, 2019. http://dx.doi.org/10.1109/icict46931.2019.8977644.

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Prabakaran, G., R. Bhavani, and S. Sankaran. "Dual Wavelet Transform in Color Image Steganography Method." In 2014 International Conference on Electronics and Communication Systems (ICECS). IEEE, 2014. http://dx.doi.org/10.1109/ecs.2014.6892512.

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Munoz-Ramirez, David O., Volodymyr I. Ponomaryov, Rogelio Reyes-Reyes, and Clara Cruz-Ramos. "Parallel steganography framework for hiding a color image inside stereo images." In SPIE Commercial + Scientific Sensing and Imaging, edited by Nasser Kehtarnavaz and Matthias F. Carlsohn. SPIE, 2017. http://dx.doi.org/10.1117/12.2262163.

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Mondal, Saikat, Rameswar Debnath, and Borun Kumar Mondal. "An improved color image steganography technique in spatial domain." In 2016 9th International Conference on Electrical and Computer Engineering (ICECE). IEEE, 2016. http://dx.doi.org/10.1109/icece.2016.7853987.

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