Developing a new adaptive satellite images classification technique, based on a new way of merging between regression line of best fit and new empirical conditions methods. They are supervised methods to recognize different land cover types on Al habbinya region. These methods should be stand on physical ground that represents the reflection of land surface features. The first method has separated the arid lands and plants. Empirical thresholds of different TM combination bands; TM3, TM4, and TM5 were studied in the second method, to detect and separate water regions (shallow, bottomless, and very bottomless). The Optimum Index Factor (OIF) is computed for these combination bands, which realized the higher OIF value with low correlated from other TM combination bands. This study was performed using ArcGIS9.3, ENVI 4.5 softwares and MATLAB7.9b language.
Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.
The Tel Hajar formation in the studied area has been divided into five microfacics units:
1) Fine hiogenic dolomite facies.
2) Sandy rich dolomite facies.
3) Dolomite diagenetic facies.
4) Recrystal1ized wackestone in microfacies.
5) Mudsione facies.
Microfacics reflect shallow marine water with open Circulation in the lower part of the formation and the environment of the upper is enclosed between upper tide and tide. The most important diagenesis was recrystallization and spary calcite deposit inside fossils chambers and pores.
Magnetic Resonance Imaging (MRI) is one of the most important diagnostic tool. There are many methods to segment the
tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment the brain with high precision. In this project, the unsupervised classification methods have been used in order to detect the tumor disease from MRI images. These metho
... Show MoreThis study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula
... Show MoreAbstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w
... Show MoreA total of 437 individuals of Turbellarin Platyhelminthes were sorted from benthic samples collected monthly for a period of seven months( April to November 2013 ) from AL-Dalmage lake, a part of middle section for main outfall drain south of Baghdad. They were identified as Gyratrix hermaphroditus, Stenostomum leucops ,Stenostomum unicolar and Stenostomum bryophilum ,The relative abundance of worms decreased during hot season which (May to September) ,where they start rising again. The species were studied alive , the identification criteria were illustrated by photos. G. hermaphroditus was the most abundant species among the four species.