Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region

Khan, Sahib

doi:10.11591/ijece.v8i1.pp379-389

Cited by 35 publications

(21 citation statements)

References 25 publications

(26 reference statements)

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“…The agency group is used to determine the process of the desired goals in the search space to resolve the problem [12]. Sahib Khan and Tiziano Bianchi suggested an Ant colony optimazation (ACO) to hide secret data it is used to discover complicated region of cover picture, after which least significant bits (LSB) exchange is used to hide the confidential information in pixels of the detected complex areas [13].…”

Section: Related Workmentioning

confidence: 99%

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Neamah¹,

Abed²,

Abbood³

2020

IJECE

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At the moment, with the great development of information and communications technology, the transfer of confidential and sensitive data through public communications such as the Internet is very difficult to keep them from hackers and attackers. Therefore, it is necessary to work on the development of new and innovative ways to transfer such information and protect it to ensure that it reaches the desired goal. The goal of a new technique to hide information design not only hides the secret message behind the center cover, but it also provides increased security. The most common way to transfer important and confidential data is through embedding it into cover medium files in a way that does not affect the accuracy of the carrier file, which is known as hiding. In this paper, encryption and concealment techniques were used to protect data transferred from attackers. The proposed method relied on encryption of confidential information using the encryption key and the Xnor gate, after which the encrypted information was hidden in a color image using the LSB algorithm. The method of concealment depends on the extraction of chromatic channels of three RGB for each pixel and specifying the channel in which the bit of the encryption message will be hidden. Some metrics have been adopted to measure the quality of the resulting picture after hiding as PSNR and MSE, and achieve good results.

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Section: Related Workmentioning

confidence: 99%

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Neamah¹,

Abed²,

Abbood³

2020

IJECE

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“…This function is mostly heuristic and it assigns a value which shows how good an edge is [22]. If the distance should be minimised, ηr,s can be defined as, The pheromone phase is used for the communication between the artificial ants and it helps to make decisions [23,24]. Pheromone evaporation and deposit are the major components in this phase.…”

Section: Ant Colony Optimisationmentioning

confidence: 99%

Optimal design of adaptive power scheduling using modified ant colony optimization algorithm

Joy

Krishnakumar

2020

IJECE

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For generating and distributing an economic load scheduling approach, artificial neural network (ANN) has been introduced, because power generation and power consumption are economically non-identical. An efficient load scheduling method is suggested in this paper. Normally the power generation system fails due to its instability at peak load time. Traditionally, load shedding process is used in which low priority loads are disconnected from sources. The proposed method handles this problem by scheduling the load based on the power requirements. In many countries the power systems are facing limitations of energy. An efficient optimization algorithm is used to periodically schedule the load demand and the generation. Ant colony optimization (ACO) based ANN is used for this optimal load scheduling process. The present work analyse the technical economical and time-dependent limitations. Also the works meets the demanded load with minimum cost of energy. Inorder to train ANN back propagation (BP) technics is used. A hybrid training process is described in this work. Global optimization algorithms are used to provide back propagation with good initial connection weights.

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“…The detail information corresponds to a differencing operation of a signal is fetched by the high pass filter while low pass filter gets the raw information corresponding to the averaging operator of the signal. Lastly, the resultant output of the filtering operation is divided by two [24,33,41]. For de-noising HAAR wavelet on HH band was applied because of it is computational fast instead of Cohen-Daubechies-Feauveas wavelet.…”

Section: Up-sampling Image Ih(n)mentioning

confidence: 99%

“…The state-of-the-art technique for image SR is the adjusted anchored neighborhood regression (A+) and the anchored neighborhood regression (ANR) [23]. There are numerous techniques used for the image super resolution using sparse representation techniques [24].The advantages of spatial and wavelet domain-based algorithm have been exploited here by combining them. The regularity of the natural images is utilized in the wavelet domain, however, to obtain the super-resolved images with sharp edges after up-sampling can only be possible by using the spatial domain-based algorithm [25][26][27].Contemporaneously, the sparsity-represented signals have gained much importance in the field of computer vision.…”

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confidence: 99%

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Single Image Super Resolution Technique: An Extension to True Color Images

et al. 2019

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The super-resolution (SR) technique reconstructs a high-resolution image from single or multiple low-resolution images. SR has gained much attention over the past decade, as it has significant applications in our daily life. This paper provides a new technique of a single image super-resolution on true colored images. The key idea is to obtain the super-resolved image from observed low-resolution images. A proposed technique is based on both the wavelet and spatial domain-based algorithms by exploiting the advantages of both of the algorithms. A back projection with an iterative method is implemented to minimize the reconstruction error and for noise removal wavelet-based de-noising method is used. Previously, this technique has been followed for the grayscale images. In this proposed algorithm, the colored images are taken into account for super-resolution. The results of the proposed method have been examined both subjectively by observation of the results visually and objectively by considering the peak signal-to-noise ratio (PSNR) and mean squared error (MSE), which gives significant results and visually better in quality from the bi-cubic interpolation technique.

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Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region

Cited by 35 publications

References 25 publications

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Optimal design of adaptive power scheduling using modified ant colony optimization algorithm

Single Image Super Resolution Technique: An Extension to True Color Images

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