This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one pixel-wide lines. Finally, the Fusion technique was used to merge the results of the Histogram Equalization process with the Skeletonization process to obtain the new high contrast images. The proposed method was tested in different quality images from National Institute of Standard and Technology (NIST) special database 14. The experimental results are very encouraging and the current enhancement method appeared to be effective by improving different quality images.
This research aims at calculating the optimum cutting condition for various types of machining methods, assisted by computers, (the computer program in this research is designed to solve linear programs; the program is written in v. basic language). The program obtains the results automatically, this occur through entering the preliminary information about the work piece and the operating condition, the program makes the calculation actually by solving a group of experimental relations, depending on the type of machining method (turning, milling, drilling). The program was transferred to package and group of windows to facilitate the use; it will automatically print the initial input and optimal solution, and thus reduce the effort and t
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KE Sharquie, AA Noaimi, SD Hameed, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 15
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The buildup factor of cylindrical samples (shields) for Brass, Copper & lead (Brass, Cu, Pb (was studied, where buildup factor were calculated with thickness between (0-12) m.f.p. for Co60 and Cs137sources with activities (30) & (41) MBq respectively , using scintillation detector NaI(T?) with (3"×3")volume .The results shows increases of buildup factor for low atomic number(Z) samples where the energy of radiation source was constant, also shows increases of buildup factor with decreases the energy of radiation source. An empirical equation was obtained using Matlab7 program this equation have agreements with most obtained data for 96%.
Original Research Paper Mathematics 1-Introduction : In the light of the progress and rapid development of the applications of research in applications fields, the need to rely on scientific tools and cleaner for data processing has become a prominent role in the resolution of decisions in industrial and service institutions according to the real need of these methods to make them scientific methods to solve the problem Making decisions for the purpose of making the departments succeed in performing their planning and executive tasks. Therefore, we found it necessary to know the transport model in general and to use statistical methods to reach the optimal solution with the lowest possible costs in particular. And you know The Transportatio
... Show MoreThe petrophysical analysis is significant to determine the parameters controlling the production wells and the reservoir quality. In this study, Using Interactive petrophysics software to analyze the petrophysical parameters of five wells penetrated the Zubair reservoir in the Abu-Amood field to evaluate a reservoir and search for hydrocarbon zones. The available logs data such as density, sonic, gamma ray, SP, neutron, and resistivity logs for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5 were used to determine the reservoir properties in Zubair reservoir. The density-neutron and neutron-sonic cross plots, which appear as lines with porosity scale ticks, are used to distinguish between the three main lithologies of sandstone, limesto
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