Informatics Publishing Limited

Ahmad M. Odat ¹, Mohammed A. Otair ²

Affiliations
1 Faculty of Science and Information Technology, Irbid National University, Irbid-Jordan, JO
2 Faculty of Computer Sciences and Informatics, Amman Arab University, Amman-Jordan, JO

Abstract

Background/Objective: Manipulation of sensitive images is a very important issue in modern transmission and storage. The objective of this study is to achieve the protection by applying a modified steganography method. Findings: The proposed method uses modified Least Significant Bit (LSB) algorithm which depends on segmentations of the secret image bits and distributing it through the odd bytes of the cover image, which in turn must be 16 time the size of the secret image in order to increase the level of protection. Improvements: Experimental results show that the levels of hiding capability using the proposed algorithm are improved.

Keywords

Image Processing, Least Significant Bit, Segmentation, Steganography.

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Mohammed A. Otair ¹, Ammar N. A. Alnajjar ¹, Ahmad Odat ²

Affiliations
1 Faculty of Science and Information Technology, Irbid National University, JO
2 Faculty of Computer Sciences and Informatics, Department of Computer Sciences, Amman Arab University, Amman - 11953, JO

Abstract

Background/Objective: Edge detection is considered as one of the most important fields in extracting critical features in an automatic image analysis. Edge detection has several methods in the sides of global, and the evaluation of these methods in perfect way is not available as it can be in an automatic way. Methods/Analysis: This paper displays a new process based on the one of the most dynamic techniques for new automatic edge detection evaluation based on semi-optimal edge detector. The main advantages of the proposed method are the evaluation of any edge detection methods with results to know which the best edge detection technique is. Findings: This paper shows an automatic experimental evaluation results for each technique of edge detection by the results of the algorithm with several preferable edge detection methods, like Sobel, Roberts, Prewitt, Laplacian of Gaussian (LOG) and Canny to get real images. After that, applying standard deviation with median filter to smooth image and get rid of the noisy pixel to perform an ideal images. Improvement: Finally, applying Pratt measure for each method of edge detection separately used to get the final results of the evaluation algorithm in terms of an automatic method for edge detection evaluation based on semi-optimal edge detector.

Keywords

Edge detection, Laplacian of Gaussian, Median Filter, Standard Deviation.

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