زينب راضي موسى المجتومي

اطروحة دكتوراه

Digital information has spread over the world; this digital information requires protection from sly activities when sent from one device to another over the wireless network, so we used the encryption algorithms to save this information. In this paper, we used algebra a significant milestone in Mathematics. In actually, it is one of the most interesting topics of Mathematics and regular practice of the topics of algebra can help develop in increase power of encryption. The proposed method includes ARZ-algebra, and application of ARZ-algebra in RC6 algorithm. Propose an encryption method that depends primarily on the sensitivity of the key and the randomness of the encryption. Rivest Cipher 6 (RC6) is block cipher algorithm which used in ARZ-algebra to the encryption biometric information. RC6 is improvements over RC5. It’s satisfied the requirements of AES algorithm. It satisfies confusion and diffusion. Dataset used are ORL, CMU, MMI, HZFD, Casia iris, fingerprint, face94. Note through the security analysis of the algorithm that it has strength in the face of hostile attacks based on the randomness of the encryption and the sensitivity of the key and in view of the measure’s values in addition to its execution time, which not exceed a minute. To estimate accuracy of encryption and decryption data, used some tests such that PSNR=inf, SNR=0, MSE=0, RMSE=0.

The aim of this paper is to introduce and study new algebraic structure, called ARZalgebra and investigate some of its properties. We give the notion of atom, subalgebra, ideal and ARZ-ideal of ARZ-algebra and quotient ARZ-Algebras, homomorphism, several theorems, properties are stated and proved.

In the last decades, there has been a stronger focus on security around the world. One of the important issues in security is the need for correct authentication of persons. Traditional methods of establishing a person’s identity include passwords, keys or identification cards, but these surrogate representationsof identity can easily be lost shared, manipulated or stolen there by compromising the intended security. In this paper we present a new approach for face recognition using Singular Values Decomposition (SVD) to extract relevant face features and Edge detection using Markov basis .The system consists of six steps is edge detection for input images,image resize, image merge,segmentation of images,SVD to feature extraction and classification by use Euclidian distance to select face image. Edge detection is one of the basic steps in image processing, image pattern recognition, image analysis and computer vision techniques. It is solving many complex problems, edge is determined on the basis of the boundary between two different areas of color intensity in the image. In this paper, the proposed method of detecting the edge was used to detect facial expressions that has found by H.H.Abbas and Z.R.Mousa in 2017, the results of using this suggested method to color image or gray image is more accurate and clarity than traditional methods. All images in database will change it size to improve the result and increment recognition ratio. All images implementation the segmentation for feature extraction for each part in image, this segmentation increases the feature the extraction of image then applies SVD algorithm on each part from segmentation image and tack features( U )and features (S ). Finally we use euclidean distance to classify the face images . The system has been evaluated on five databases The result of a classification ratio in the overall system when the use of ORL database has been obtained on ratio 97.5%, CMU database has been obtained on ratio 100%, MMI face database has been obtained on ratio 100%, face94 database has been obtained on ratio 100% and HZFD(Husein and Zainab Face Database) has been obtained on ratio 100 %.

رسالة الماجستير

Edge detection is an important task in any image processing application. An edge is a boundary between two disjoint regions. To recognize any unusual objects or growths automatically in medical images, proper edge detection is a crucial step for efficient medical image . Medical images edge detection is an important work for object recognition of the human organs . Edge is detected according to trad methods, but they are not so good for noise medical image edge detection. In this paper, a proposed filter is used to detect the edge of the medical image has been the application of the proposed filter on the actual pictures or fact to find the edge of a high-resolution and this filter has been created by Markov Basis and Laplace filter. It has been observed that the proposed edge detection method performs better than Sobel, Prewitt, Rroberts and Cannys edge detection algorithms.