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Automatic Detection and Recognition of Car Plates Based on Cascade Classifier
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The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the accuracy was 99.8%.

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Influence of Gold Concentration on the Main Detection Parameters of Ge-Au Photoconductive Detector
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Ge-Au infrared photoconductive detection was prepared from germanium single crystal which were doped with different gold concentration using thermal evaporation. The spectral resonsivity (Rλ), spectral detectivity (D*) were determined as function of wavelength, also the resistance, conductivity in dark and with illumination to infrared radiation, the gain and relative photo response have been measured with different gold concentration. Remarkable improvements in the photoresponse gain were observed for the highest resistance specimen at the expense of spectral detectivity values.

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Fingerprints Identification and Verification Based on Local Density Distribution with Rotation Compensation
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The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Secure Big Data Transmission based on Modified Reverse Encryption and Genetic Algorithm
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      The modern systems that have been based upon the hash function are more suitable compared to the conventional systems; however, the complicated algorithms for the generation of the invertible functions have a high level of time consumption. With the use of the GAs, the key strength is enhanced, which results in ultimately making the entire algorithm sufficient. Initially, the process of the key generation is performed by using the results of n-queen problem that is solved by the genetic algorithm, with the use of a random number generator and through the application of the GA operations. Ultimately, the encryption of the data is performed with the use of the Modified Reverse Encryption Algorithm (MREA). It was noticed that the

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Publication Date
Wed Apr 17 2019
Journal Name
Iraqi Journal Of Science
Fabrication and Enhancement UV Photodiode Based on Mg-Doped ZnO Nanorods Films
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Magnesium-doped Zinc oxide (ZnO: Mg) nanorods (NRs) films and pure Zinc oxide deposited on the p-silicon substrates were prepared by hydrothermal method. The doping level of the Mg concentration (atoms ratio of Mg to Zn was chosen to be 0.75% and 1.5%. X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDX) were performed to characterize the prepared films. X-ray diffraction analysis showed a decrease in the lattice parameters of the Mg-doped ZnO NRs. Under 10V applied bias voltage, the responsivity of p-n junction UV photodiode based on pure ZnO and Mg: ZnO with doping ratio (0.75% and 1.5%) was 0.06 A/W and (0.15A/W and 0.27A/W) at UV illumination of wavelength 365 nm respectively, 0.071 A/W and (0.084A/W and 0.11A/W) fo

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Sat Jul 01 2023
Journal Name
Int. J. Advance Soft Compu. Appl,
Arabic and English Texts Encryption Using Proposed Method Based on Coordinates System
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Publication Date
Mon Apr 15 2024
Journal Name
Journal Of Engineering Science And Technology
Text Steganography Based on Arabic Characters Linguistic Features and Word Shifting Method
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In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

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Publication Date
Sun Jun 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Digital Watermarking in Color Image Based On Joint Between DCT and DWT
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The massive distribution and development in the digital images field with friendly software, that leads to produce unauthorized use. Therefore the digital watermarking as image authentication has been developed for those issues. In this paper, we presented a method depending on the embedding stage and extraction stag. Our development is made by combining Discrete Wavelet Transform (DWT) with Discrete Cosine Transform (DCT) depending on the fact that combined the two transforms will reduce the drawbacks that appears during the recovered watermark or the watermarked image quality of each other, that results in effective rounding method, this is achieved by changing the wavelets coefficients of selected DWT sub bands (HL or HH), followed by

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Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Encryption Algorithm Based on Chaotic Neural Network and Random Key Generator
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This work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m

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