The Use of Quadtree Range Domain Partitioning with Fast Double Moment Descriptors to Enhance FIC of Colored Image

In this paper, an enhanced fractal image compression system (FIC) is proposed; it is based on using both symmetry prediction and blocks indexing to speed up the blocks matching process. The proposed FIC uses quad tree as variable range block partitioning mechanism. two criteria’s for guiding the partitioning decision are used: The first one uses sobel-based edge magnitude, whereas the second uses the contrast of block. A new set of moment descriptors are introduced, they differ from the previously used descriptors by their ability to emphasize the weights of different parts of each block. The effectiveness of all possible combinations of double moments descriptors has been investigated. Furthermore, a fast computation mechanism is introduced to compute the moments attended to improve the overall computation cost. the results of applied tests on the system for the cases “variable and fixed range” block partitioning mechanism indicated that the variable partitioning scheme can produce better results than fixed partitioning one (that is, 4 × 4 block) in term of compression ratio, faster than and PSNR does not significantly decreased

A Comparative Study and Analysis of Query in Encrypted Databases

تعد البيانات اليوم هي الموجود الرئيسي للشركات وأعمالها. عادة ما يتم تخزين هذه البيانات في قاعدة البيانات. يجب أن تكون جميع أنظمة قواعد البيانات قادرة على الاستجابة لطلبات الحصول على معلومات من المستخدم وهي استعلامات العمليات. هناك حاجة إلى خوارزميات التشفير التي توفر القدرة على الاستعلام عبر قاعدة البيانات المشفرة وتتيح تحسين تشفير وفك تشفير البيانات. ومع ذلك ، تطبيق خوارزميات التشفير على قاعدة البيانات المشفرة يعتبر التحدي الذي ينشأ هو في  انخفاض اداء النظام الناتج عن نشر خوارزمية التشفير في وقت التشغيل. لذلك ، تعرض هذه الورقة معظم الأعمال الحديثة التي تم إجراؤها على معالجة الاستعلام في  قاعدة البيانات المشفرة وتحليلها لتوضيح تحليل الأداء ، بناءً على مقاييس أداء مختلفة في كل عمل ذي صلةData is the main asset of the modern companies and their businesses. Typically, it is stored in the data-base. Every database system has to be capable of responding to information requests from users, which is queries of the process. Encryption mechanisms are required, which give the capability to the query over the encrypted data-base and permit the optimization of data encryption and decryption. However, applying encryption algorithms on Encrypted database then challenge arises that the efficiency of the system degrades on deploying encryption algorithm on the runtime. Therefore, this paper presents most of the recent works that have been conducted on the query preprocessing of encrypted database and analyzes them to clarify the performance analysis, based on different performance metrics in each related work

ANEW TECHNIQUE BY USING INVERTED TABLES AND 3D BOX FOR EFFICIENT QUERYING OVER AN ENCRYPTED DATABASE

The increase in the amount of data in encrypted databases has caused problems in data processing and retrieval time. In traditional query processing methods, there are many difficulties in execute query over an encrypted database because it is time- consuming. In this paper, proposes technique for querying encrypted databases records, allows authorized users to execute queries without decrypting all the records of the encrypted database. In this technique, inverted tables include the numbers of 3D box cover locations that were created to enhance and speed up the retrieval time of query and improve an approach of data embedding according to the random 3D box. The proposed method has been examined on the Iraqi voter encrypted Database. The retrieval time in (second, millisecond) has been computed for the traditional method of query processing and proposed technique that using inverted tables. The retrieval time of query executing of proposed techniques without retrieval of all the records of the encrypted database is 10.870 (seconds, millisecond) where the retrieval time of query executing of conventional method that’s retrieval of all the records of the encrypted database is 40.682 (seconds, millisecond)

Generate Random Image-Key using Hash Technique

Random image is very useful to be used as a source for clipping randomnesssession keys in cryptography. In this paper a new algorithm is proposed to generaterandom image .The random image is generated by mixing initialization vector withnormal digital image; the mixing process is applied in the same way as HASHtechnique. A special cryptography algorithm for generating random numbers isused to generate initialization vector. This proposed algorithm is capable ofgenerating random image that can meet security requirements of cryptographicalgorithms

Generate Animated CAPTCHA Based on Visual Cryptography Concept

CAPTCHA is a standard security technology. To date, the most commonly used are various types of visual CAPTCHAs, in which a challenge often appears as an image of distorted text that the user must decipher. The proposed scheme is used visual cryptography encryption protocol to encrypt CAPTCHA image in perfectly secure way, such that only the human visual system can easily decrypt the CAPTCHA image with animated arrangement. Numbers of blurring image process are implemented on the CAPTCHA images, to make this test difficult for current computer systems. The new animated CAPTCHA is more secure than the currentversions and easier for humans to pass

Classification of Anemia Images Based on Principal Component Analysis (PCA)

Blood cells are composed of erythrocytes (Red Blood Cells (RBCs)), the shape of RBC changes when the body suffers from different diseases such as Anemia. Classification of such diseases helps the medical technician to decide the type of Anemia in Laboratory analyzes in the hospitals. This paper proposed an automatic classification algorithm, which discriminates the different types of Anemia using Principal Component Analysis (PCA) algorithm and Decision tree. The proposed algorithm consists of four steps, at the first step preprocessing steps are applied on the RBC image, these RBC images then segmented in the second step, features are extracted using moment invariant in third step, this features are considered input to PCA so as to produced features vectors, at a final step features vector are inputted to Decision Tree to classify RBC image. Best classifications rates are (92%) obtained when using PCA algorithm compared with (74.1 %) which are obtained without applying PCA algorithm