The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of the right features leads to high accuracy in the system diagnostics and vice versa. The proposed system collect images of different crop (Rice, cotton and tomato) disease, we will enter the images of cropping them , then Re-size the images to fixed size, then improve the image through Fuzzy histogram equalization (FHE) , then perform image segmentation using color based K-means and finally compare the methods of features extraction (Percentage of Leaf Area Infected (PI),Texture-Based Features, Color Moments, Features obtained by Color Co-occurrence Method and Shape based Features) we found that the use of 4 methods together (Percentage of Leaf Area Infected (PI),Texture-Based Features, Color Moments and Shape based Features) produce excellent result..
Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet
... Show MoreA nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.
Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique wh
... Show MoreIn this paper, we devoted to use circular shape sliding block, in image edge determination. The circular blocks have symmetrical properties in all directions for the mask points around the central mask point. Therefore, the introduced method is efficient to be use in detecting image edges, in all directions curved edges, and lines. The results exhibit a very good performance in detecting image edges, comparing with other edge detectors results.
conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation.
The research examines the mechanism of application of )ISO 21001: 2018( in the Energy Branch- Electromechanical Engineering at the University of Technology to achieve the quality of the educational service to prepare the branch to obtain the certificate of conformity with the requirements of) ISO 21001: 2018(, the necessary data were collected Depending on the (CHEKLIST) of (ISO 21001: 2018), field interviews and records of the concerned department, The researchers reached a number of results, the most prominent of which was the adoption of high quality leadership leaders and their willingness to implement the standard requirements, The university has a basic structure that qualifies it to implement the international standard, as
... Show MoreGreen synthesis is depending on preparation of nano composited SiO2/V2O5 by using the modified sol-gel method depending on rice husk ash as a source for the extraction of silica gel and the product powder of nano composited SiO2/V2O5 characterization by many techniques such as X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FESEM), and N2 adsorptions/desorption isotherms (BET). This study also includs the biological effectiveness of SiO2/V2O5 and its effect on inhibiting bacterial growth after the prepared nanomaterial was applied to wound dressings, which gave a promising result for its use as
... Show MoreCoupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range
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