Preferred Language
Articles
/
bsj-2553
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
...Show More Authors

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Strongly K-nonsingular Modules
...Show More Authors

       A submodule N of a module M  is said to be s-essential if it has nonzero intersection with any nonzero small submodule in M. In this article, we introduce and study a class of modules in which all its nonzero endomorphisms have non-s-essential kernels, named, strongly -nonsigular. We investigate some properties of strongly -nonsigular modules. Direct summand, direct sums and some connections of such modules are discussed.        

View Publication Preview PDF
Crossref
Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Numeral Recognition Using Statistical Methods Comparison Study
...Show More Authors

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

View Publication Preview PDF
Crossref
Publication Date
Tue Jan 30 2018
Journal Name
Iraqi Journal Of Science
Improve the Spatial Resolution of Multispectral satellite Image using Different Image Sharpening Techniques
...Show More Authors

The process of combining the significant information from a series of images into a single image called image sharpening or image fusing, where the resultant fused image will be having more spatial and spectral information than any of the input images. in this research two images of the same place in different spatial resolution have been used the first one was panchromatic and the second image was multispectral with spatial resolution 0.5m and 2 m respectively. These images were captured by world view-2 sensor. This research resent four pan sharpening methods like (HSV, Brovey (color normalizes) , Gram shmidt and PCA)these methods were used to combine the adopted images to get multispectral image

... Show More
View Publication Preview PDF
Publication Date
Thu Aug 30 2018
Journal Name
Journal Of Engineering
An Optimum Strategy for Producing Precise GPS Satellite Orbits using Double-Differenced Observations
...Show More Authors

Both the double-differenced and zero-differenced GNSS positioning strategies have been widely used by the geodesists for different geodetic applications which are demanded for reliable and precise positions. A closer inspection of the requirements of these two GNSS positioning techniques, the zero-differenced positioning, which is known as Precise Point Positioning (PPP), has gained a special importance due to three main reasons. Firstly, the effective applications of PPP for geodetic purposes and precise applications depend entirely on the availability of the precise satellite products which consist of precise satellite orbital elements, precise satellite clock corrections, and Earth orientation parameters. Secondly, th

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
The Effect of Using the Different Satellite Spatial Resolution on the Fusion Technique
...Show More Authors

      Bilinear interpolation and use of perceptual color spaces (HSL, HSV, LAB, and LUV) fusion techniques are presented to improve spatial and spectral characteristics of the multispectral image that has a low resolution to match the high spatial resolution of a panchromatic image for different satellites image data (Orbview-3 and Landsat-7) for the same region. The Signal-to-Noise Ratio (SNR) fidelity criterion for achromatic information has been calculated, as well as the mean color-shifting parameters that computed the ratio of chromatic information loss of the RGB compound inside each pixel to evaluate the quality of the fused images. The results showed the superiority of HSL color space to fuse images over the rest of the spac

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (3)
Scopus Crossref
Publication Date
Fri Sep 30 2016
Journal Name
Australian Journal Of Basic And Applied Sciences
Programming Exam Questions Classification Based On Bloom’s Taxonomy Using Grammatical Rule
...Show More Authors

Preview PDF
Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
...Show More Authors

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
New Tasseled Cap Classification Technique using Landsat-8 OLI Image Bands
...Show More Authors

The tasseled cap transformation (TCT) is a useful tool for compressing spectral data into a few bands associated with physical scene characteristics with minimal information loss. TCT was originally evolved from the Landsat multi-spectral scanner (MSS) launched in 1972 and is widely adapted to modern sensors. In this study, we derived the TCT coefficients for operational land imager (OLI) sensor on-board Landsat-8 acquired at 28 Sep.2013. A newly classification method is presented; the method is based on dividing the scatterplot between the Greenness and the Brightness of TCT into regions corresponding to their reflectance values. The results from this paper suggest that the TCT coefficient derived from the OLI bands at September is the

... Show More
View Publication Preview PDF
Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
...Show More Authors

View Publication
Scopus (4)
Crossref (4)
Scopus Crossref
Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
...Show More Authors

The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref