Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including human computer interfaces. The proposed method includes sequential stages of object segmentation, feature extraction, action detection and then action recognition. Effective results of human actions using different features of unconstrained videos was a challenging task due to camera motion, cluttered background, occlusions, complexity of human movements, and variety of same actions performed by distinct subjects. Thus, the proposed method overcomes such problems by using the fusion of featur

In this paper an authentication based finger print biometric system is proposed with personal identity information of name and birthday. A generation of National Identification Number (NIDN) is proposed in merging of finger print features and the personal identity information to generate the Quick Response code (QR) image that used in access system. In this paper two approaches are dependent, traditional authentication and strong identification with QR and NIDN information. The system shows accuracy of 96.153% with threshold value of 50. The accuracy reaches to 100% when the threshold value goes under 50.

Digital forensic is part of forensic science that implicitly covers crime related to computer and other digital devices. It‟s being for a while that academic studies are interested in digital forensics. The researchers aim to find out a discipline based on scientific structures that defines a model reflecting their observations. This paper suggests a model to improve the whole investigation process and obtaining an accurate and complete evidence and adopts securing the digital evidence by cryptography algorithms presenting a reliable evidence in a court of law. This paper presents the main and basic concepts of the frameworks and models used in digital forensics investigation.

          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

The revolution of multimedia has been a driving force behind fast and secured data transmission techniques. The security of image information from unapproved access is imperative. Encryptions technique is used to transfer data, where each kind of data has its own special elements; thus various methods should to be used to conserve distributing the image. This paper produces image encryption improvements based on proposed an approach to generate efficient intelligent session (mask keys) based on investigates from the combination between robust feature for ECC algebra and construction level in Greedy Randomized Adaptive Search Procedure (GRASP) to produce durable symmetric session mask keys consist of ECC points. Symmetric behavior for ECC

Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio