The context of multibiometric plays a pivotal role in enhancing an identification system, since a biometric system is now the most physical way of identifying and verifying individuals. The feature of multibiometric could be merged to produce identification information. However, unimodal biometric systems suffer from different types of breaching. Thus, mixing biometrics with cryptography leads to overcome small variations existing between diverse acquisitions of the same biometric in order to produce the robust system. In this paper, a new robust multibiometric system is proposed to create a random key from person multibiometric, facial and fingerprint images which are used simultaneously to produce this key. Several manipulations are made on compactness information for these two images to get a unique key for each person. The generated random key can be used for electronic numbers, passport identification, civil identification card, and it could be used as seeds for pseudo-random number generators. The multi-biometric system operates on two images, faces and fingerprints, by partitioning each image into four parts and taking the highest density for each one, XOR these parts; diffusions process is applied on these parts including permutation and thresholding to produce a random key. The generated key cannot be revocable that passed through randomness tests to ensure whether the generated key is accepted as true. Thus, the results of the tests are passed and presented that all generated keys are accepted to be random and unpredictable binary sequences and hence they can be used efficiently.
Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers. The experiment’s
... Show MoreHumanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking rob
... Show MoreA new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λmax 496nm.The linearity range of sulfamethoxazole was 3-100 μg. mL-1, with (LOD) was 0.593 μg. mL-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of
... Show MoreThe operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.
In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of drought, normal flow, and during floods. Moreover, the cases of hypothetical op
... Show MoreThe influence of bias current on the bandwidth of chaotic signals in semiconductor lasers by optical feedback has been studied experimentally and numerically. The measured data reveal that the bandwidth increase when the system becomes chaotic and this chaotic signal has a broadband spectrum so it can be used as a carrier for the quantum key. Mixing chaotic signal and quantum key make a very small change in chaotic bandwidth that does not affect the security of data transmitted.
In this research paper, a new blind and robust fingerprint image watermarking scheme based on a combination of dual-tree complex wavelet transform (DTCWT) and discrete cosine transform (DCT) domains is demonstrated. The major concern is to afford a solution in reducing the consequence of geometric attacks. It is due to the fingerprint features that may be impacted by the incorporated watermark, fingerprint rotations, and displacements that result in multiple feature sets. To integrate the bits of the watermark sequence into a differential process, two DCT-transformed sub-vectors are implemented. The initial sub-vectors were obtained by sub-sampling in the host fingerprint image of both real and imaginary parts of the DTCWT wavelet coeffi
... Show MoreSpatial and frequency domain techniques have been adopted in this search. mean
value filter, median filter, gaussian filter. And adaptive technique consists of
duplicated two filters (median and gaussian) to enhance the noisy image. Different
block size of the filter as well as the sholding value have been tried to perform the
enhancement process.
<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in
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