Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Arabic text

Arabic Language Text Steganography Based on Singular Value Decomposition (SVD)

Hanaa M. Ahmed; a A. A. Khohder; Maisa

Engineering and Technology Journal, 2016, Volume 34, Issue 5, Pages 629-637

With the fast development of internet innocent over communication in the network environment has become an important research direction. Steganography means that secret information is embedded into cover data imperceptibly for transmission. Linguistic Steganography covers all the techniques that deal with using written natural language to hide the secret message. This paper, presents a linguistic steganography for Arabic language texts, using Kashida and Fast Fourier Transform on the basis of using a new technique entitled Random Singular Value Decomposition Image as a location to hide a secret message. The proposed approach is an attempt to present a transform linguistic steganography using levels for hiding to improve implementation of kashida, and improve the security of the secret message by using Random Singular Value Decomposition Image. The proposed algorithm achieves typical steganography properties such as capacity, security, transparency, and robustness.

An Efficient Image Thresholding Method for Arabic Handwriting Recognition System

Alia Karim Abdul Hassan; Mustafa Salam Kadhm

Engineering and Technology Journal, 2016, Volume 34, Issue 1, Pages 26-34

Image preprocessinghas assumed an essential part ofhandwriting recognition system. The main primary stage of the image preprocessing is thresholding.Aneffectivethresholdingmethodis based on Fuzzy C-Means clustering (FCM) for Arabic Handwriting Recognition system (AHR) has been proposed in this paper. Since thresholding stage in AHR isimperative to reduce the dimensionality of image to remove the undesirableinformation (noise)then increase the processing speed of the AHR system. The algorithm is performing by feedingthe intensity of the pixel value of the image pixels into the FCM clustering algorithm. Exploratory results with artificial and real life images show thatthe proposed method gives better accuracy and good efficiency than the current methods.