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Journal ArticleDOI

A high payload steganographic algorithm based on edge detection

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TLDR
A novel steganography approach based on the combination of LSB substitution mechanism and edge detection is proposed that achieves a much higher payload and better visual quality than those of state-of-the-art schemes.
About
This article is published in Displays.The article was published on 2017-01-01. It has received 87 citations till now. The article focuses on the topics: Payload (computing) & Edge detection.

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Citations
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Journal ArticleDOI

An Enhanced LSB-Image Steganography Using the Hybrid Canny-Sobel Edge Detection

TL;DR: In this research paper, Canny and Sobel detectors are combined to get a wider edge area for greater payload of messages while maintaining imperceptibility of stego-images.
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Digital image steganography and steganalysis: A journey of the past three decades

TL;DR: This study aims to present an exhaustive scrutiny of various ISTs from the classical to recent developments in the spatial domain, with respect to various image steganographic metrics.
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A Combination of Inverted LSB, RSA, and Arnold Transformation to get Secure and Imperceptible Image Steganography

TL;DR: This paper proposes combing Arnold’s transformation with RSA and subsequently embedding the result in a cover image with inverted two-bit LSB steganography, which replaces two bits in the bit plane of the cover images with message bits, which can provide twice the capacity of the previous method.
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High-Capacity Image Steganography with Minimum Modified Bits Based on Data Mapping and LSB Substitution

TL;DR: This study proposes a novel steganography method with data mapping strategy which can reduce the number of bits modification per pixel and provides security against basic Regular and Singular groups Steganalysis and histogram steganalysis detection attacks.
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Improved payload capacity in LSB image steganography uses dilated hybrid edge detection

TL;DR: The proposed dilated hybrid edge detection on the three most significant bits (MSB) pixels of cover images with the aim of expanding the edge area so as to increase the data embedding capacity in image steganography succeeded in improving the quality of imperceptibility.
References
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Journal ArticleDOI

A Computational Approach to Edge Detection

TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
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Techniques for data hiding

TL;DR: This work explores both traditional and novel techniques for addressing the data-hiding process and evaluates these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.
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Hiding data in images by simple LSB substitution

TL;DR: By applying an optimal pixel adjustment process to the stego-image obtained by the simple LSB substitution method, the image quality of the stega-image can be greatly improved with low extra computational complexity.
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Spread spectrum image steganography

TL;DR: A new method of digital Steganography, entitled spread spectrum image steganography (SSIS), which hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range.
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Image hiding by optimal LSB substitution and genetic algorithm

TL;DR: A novel method to embed important data in the host image so that the interceptors will not notice about the existence of the data is developed and an improved hiding technique is developed to obtain a high-quality embedding result.
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