Edge Based Image Steganography: Problems and Solution

Rashid, Rasber; Majeed, Taban F.

doi:10.1109/iccspa.2019.8713712

Cited by 15 publications

(8 citation statements)

References 9 publications

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“…Similarly, instead of LBP, the edges of the color cover images are obtained. Then, the binary bits of the secret information is hidden in the edges discovered in the cover images [20]. Other methods of the traditional steganography methods are described below.…”

Section: A Traditional-based Steganography Methodsmentioning

confidence: 99%

Image Steganography: A Review of the Recent Advances

et al. 2021

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Image Steganography is the process of hiding information which can be text, image or video inside a cover image. The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, which has emerged as a powerful tool in various applications including image steganography, has received increased attention recently. The main goal of this paper is to explore and discuss various deep learning methods available in image steganography field. Deep learning techniques used for image steganography can be broadly divided into three categories -traditional methods, Convolutional Neural Network-based and General Adversarial Network-based methods. Along with the methodology, an elaborate summary on the datasets used, experimental set-ups considered and the evaluation metrics commonly used are described in this paper. A table summarizing all the details are also provided for easy reference. This paper aims to help the fellow researchers by compiling the current trends, challenges and some future direction in this field.

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Section: A Traditional-based Steganography Methodsmentioning

confidence: 99%

Image Steganography: A Review of the Recent Advances

et al. 2021

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“…Optimal choices often revolve around carrier mediums with high redundancy. Several commonly utilized mediums include as shown in Figure (1) [13]: Steganography is a method of concealing data for various purposes, primarily to prevent unauthorized access or awareness of a message. It finds applications in radio monitoring, automatic systems for detecting specific stego messages, and modern technologies like web hosting for secret information transfer.…”

Section: Steganography Definition and Types And Applicationsmentioning

confidence: 99%

“…Table (1) provides a comprehensive overview of various steganography types, elucidating their distinct characteristics, techniques employed, applicable file formats, and inherent challenges. Steganography, the art of covert communication, manifests through diverse forms such as Image Steganography, where data is concealed within pixel intensities of digital images.…”

Section: Steganography Definition and Types And Applicationsmentioning

confidence: 99%

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An In-Depth Analysis of Steganography Techniques: From Classical Edge Detection to Adaptive Approaches

Gh. Abdullah,

A. Hasso

2024

IRJIET

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This paper delves into the realm of steganography, focusing on the evolution of techniques employed to conceal data within digital images. Beginning with an exploration of the motivations behind information security and the role of cryptography, the paper introduces adaptive steganography as a discreet means of incorporating private data into a cover medium. The discussion then shifts to the three key factors in image steganography - resilience, capacity, and imperceptibility - forming the foundation of effective data hiding. The spatial and frequency domain methods are compared, with specific emphasis on the classical Least Significant Bit insertion and more advanced adaptive steganography techniques. The paper further introduces edge-based steganography, highlighting the advantage of manipulating edge areas for increased imperceptibility. Moving beyond definitions and types, the paper provides a comprehensive analysis of notable research works in the field, elucidating their objectives, methodologies, results, strengths, and limitations. The conclusion reflects on the dynamic landscape of steganography, acknowledging both achievements and areas for improvement.

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“…Starting from the centre pixel in the B channel, the method embedded two secret bits in the smooth pixels and three bits in the sharp pixels using the LSB method. Rashid and Majeed [33] proposed a technique that applied edge detection on the Blue component and used the edge positions as indicators of the existence of data in the Green component. This method used only the edge positions that satisfied a threshold value, which increased the security of the method.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving data hiding within colour images using hue component of HSV colour space

Hassan

Gutub

2021

CAAI Trans on Intel Tech

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Data hiding technologies aim to hide the existence of secret information within digital covers such as images by causing unnoticeable degradation to their quality. Reducing the image distortion and increasing the embedding capacity are the main points that the data hiding techniques revolved around. This article proposes two high payload embedding methods with high stego image quality using the Hue-Saturation-Value (HSV) colour model. The first method is hue-based embedding (HBE) that employs the H plane for hiding one or two bits in non-grey pixels. The second method uses the three HSV components, so it is called three-planes embedding (TPE). In TPE, one bit is hidden in the least significant bit (LSB) of V of the grey pixels, one or two bits in H of the pixels having low saturation or low brightness and one bit in the LSB of S otherwise. The experiments were conducted on 25 images and the results show that HBE hides more data on average than TPE with its quality reaching 60 dB. TPE achieves quality up to 61 dB and capacity reaches 364 Kb. TPE scores the highest capacity among six state-ofthe-art techniques in Red-Green-Blue, HSV, Hue-Saturation-Intensity and YCbCr spaces with the highest average peak signal to noise ratio midst five of them. By embedding 60, 90, and 120 Kb, this TPE attains the best average quality amid all the methods.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Edge Based Image Steganography: Problems and Solution

Cited by 15 publications

References 9 publications

Image Steganography: A Review of the Recent Advances

Image Steganography: A Review of the Recent Advances

An In-Depth Analysis of Steganography Techniques: From Classical Edge Detection to Adaptive Approaches

Improving data hiding within colour images using hue component of HSV colour space

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