Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

The present study was Conducted to evaluate the effect of amixture of three species of arbuscular mycorrhizal fungi ( Glomus etunicatum , G. leptotichum and Rhizophagus intraradices ) in Influence on the percentage of the components of NPK and protein of tomato leaves and roots infected with Fusarium oxysporum f.sp. Lycopersici wich cause Fusarial wilt disease , planted for 8 weeks in the presence of the organic matter ( peatmose) , using pot cultures in aplastic green house , Results indicated significant increase in the percentage of the elements of NK and protein of tomato leaves and roots In the control treatment (C), While the percentage of the element P was after infection with the pathogen 4 weaks after mycorrhizal colonization in al

Abstract The present study was Conducted to evaluate the effect of amixture of three species of arbuscular mycorrhizal fungi ( Glomus etunicatum , G. leptotichum and Rhizophagus intraradices ) in Influence on the percentage of the components of NPK and protein of tomato leaves and roots infected with Fusarium oxysporum f.sp. Lycopersici wich cause Fusarial wilt disease , planted for 8 weeks in the presence of the organic matter ( peatmose) , using pot cultures in aplastic green house , Results indicated significant increase in the percentage of the elements of NK and protein of tomato leaves and roots In the control treatment (C), While the percentage of the element P was after infection with the pathogen 4 weaks after mycorrhiza

This study concluded detection of Toxoplasma gondii in milk, immunologically by using Elisa and nested PCR)nPCR (based on B1 gene, also to investigate the effect of toxoplasmosis, parity, breed and flock on some milk composition in the Iraqi local and Shami goats in the middle of Iraq. A total of 80 milk samples of the lactating goats were collected. Results of this study showed the prevalence of Toxoplasmosis was 21.25% and 28.75% by Elisa and nPCR respectively without significant differences. The sensitivity of Elisa was a low (30.43%) whereas the specificity was a high (82.45%). The degree of agreement estimated by Kappa coefficient revealed a slight agreement (0.14) between two methods. The results indicated that goats infected

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

Boltzmann mach ine neural network bas been used to recognize the Arabic speech.  Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .

The  spectral  feature size is reduced by series of operations in

order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural  network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.

The neural network recognized Arabic. After Boltzmann Machine Neura l    network   training  the  system   with 

The recognition of handwritten numerals has many applications in automatic identification and cognition. This research contains three experimented scenarios to recognize the handwritten English (i.e. Arabic) numerals. In the first scenario the bilinear interpolation of the image is used, while in the second scenario and after the bilinear interpolation is being applied, the Sobel operators are applied on the resulted interpolated image. In the third scenario which represents the last one, the effect of normalization of image dimensions is tested. 550 images of handwritten numerals were tested. Three types of tests were conducted for each scenario namely: trained-set test, not-trained-set test and comprehensive-set test. Depending on the