Fingerprints are commonly utilized as a key technique and for personal recognition and in identification systems for personal security affairs. The most widely used fingerprint systems utilizing the distribution of minutiae points for fingerprint matching and representation. These techniques become unsuccessful when partial fingerprint images are capture, or the finger ridges suffer from lot of cuts or injuries or skin sickness. This paper suggests a fingerprint recognition technique which utilizes the local features for fingerprint representation and matching. The adopted local features have determined using Haar wavelet subbands. The system was tested experimentally using FVC2004 databases, which consists of four datasets, each set holds 80 fingers with 8 samples per finger. The attained test results showed encouraging system capability to recognize low quality fingerprint images although with presence of partial loss in fingerprint images.
The purpose of this study is to evaluate the hydraulic performance and efficiency of using direction diverting blocks, DDBs, fixed on the surface on an Ogee spillway in reducing the acceleration and dissipating the energy of the incoming supercritical flow. Fifteen types of DDB models were made from wood with a triangulate shape and different sizes were used. Investigation tests on pressure distribution at the DDBs boundaries were curried out to insure there is no negative pressures is developed that cause cavitation. In these tests, thirty six test runs were accomplished by using six types of blocks with the same size but differ in apex angle. Results of these test showed no negative pressures developed at the boundarie
... Show MoreA new results for fusion reactivity and slowing-down energy distribution functions for controlled thermonuclear fusion reactions of the hydrogen isotopes are achieved to reach promising results in calculating the factors that covered the design and construction of a given fusion system or reactor. They are strongly depending upon their operating fuels, the reaction rate, which in turn, reflects the physical behavior of all other parameters characterization of the system design
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The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p
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As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreKA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1
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