Preferred Language
Articles
/
lhYZAooBVTCNdQwCiY9a
Image encryption algorithm based on the density and 6D logistic map
...Show More Authors

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are generated depending on the chaotic logistic with the image density to encrypt the gray and color images, and the second stage is the decryption, which is the opposite of the encryption process to obtain the original image. The proposed method has been tested on two standard gray and color images publicly available. The test results indicate to the highest value of peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel change rate (NPCR) are 7.7268, 50.2011 and 100, respectively. While the encryption and decryption speed up to 0.6319 and 0.5305 second respectively.

Scopus Crossref
View Publication
Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Digital Color Image Watermarking Using Encoded Frequent Mark
...Show More Authors

With the increased development in digital media and communication, the need for methods to protection and security became very important factor, where the exchange and transmit date over communication channel led to make effort to protect these data from unauthentication access.

This paper present a new method to protect color image from unauthentication access using watermarking. The watermarking algorithm hide the encoded mark image in frequency domain using Discrete Cosine Transform. The main principle of the algorithm is encode frequent mark in cover color image. The watermark image bits are spread by repeat the mark and arrange in encoded method that provide algorithm more robustness and security. The propos

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Mon Sep 30 2024
Journal Name
Al-mustansiriyah Journal Of Science
A Transfer Learning Approach for Arabic Image Captions
...Show More Authors

Publication Date
Wed Jul 06 2022
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression using Polynomial Coding Techniques: A review
...Show More Authors

Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Medical Image Segmentation using Modified Interactive Thresholding Technique
...Show More Authors

Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w

... Show More
View Publication Preview PDF
Publication Date
Sat Dec 01 2018
Journal Name
Al-nahrain Journal Of Science
Image Classification Using Bag of Visual Words (BoVW)
...Show More Authors

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

View Publication Preview PDF
Crossref (23)
Crossref
Publication Date
Fri Jan 01 2016
Journal Name
Bio-inspired Computing – Theories And Applications
Image Segmentation Using Membrane Computing: A Literature Survey
...Show More Authors

View Publication
Scopus (10)
Crossref (5)
Scopus Crossref
Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding text in gray image using mapping technique
...Show More Authors

Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Sun Jan 01 2023
Journal Name
Proceedings Of International Conference On Data Science And Applications
Very Low Illumination Image Enhancement via Lightness Mapping
...Show More Authors

View Publication
Scopus (4)
Crossref (2)
Scopus Crossref
Publication Date
Tue Jun 01 2021
Journal Name
Al-nahrain Journal Of Science
Medical Image Denoising Via Matrix Norm Minimization Problems
...Show More Authors

This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma

... Show More
View Publication
Scopus (1)
Crossref (1)
Scopus Crossref