The amount of digital images that are produced in hospitals is increasing rapidly. Effective
medical images can play an important role in aiding in diagnosis and treatment, they can
also be useful in the education domain for healthcare students by
explaining with these
images will help them in their studies, new trends for image retrieval using automatic
image classification has been investigated for the past few years. Medical image
Classification can play an important role in diagnostic and teaching purposes in medicine.
For these purposes different imaging modalities are used. There are many classifications
created for medical images using both grey-scale and color medical images. In this paper,
different algorithms in every step involved in medical image processing have been studied.
One way is the algorithms of preprocessing step such as Median filter [1], Histogram
equalization (HE) [2], Dynamic histogram equalization (DHE), and Contrast Limited
Adaptive Histogram Equalization (CLAHE). Second way is the Feature Selection and
Extraction step [3,4], such as Gray Level Co-occurrence Matrix(GLCM). Third way is the
classification techniques step, which is divided into three ways in this paper, first one is
texture classification techniques, second one is neural network classification techniques,
and the third one is K-Nearest Neighbor classification techniques.
In this paper, we have use MRI brain image to determine the area of tumor in brain. The
steps started by preprocessing operation to the image before inputting it to algorithm. The
image was converted to gray scale, later on remove film artifact using special algorithm,
and then remove the Skull portions from the image without effect on white and gray matter
of the brain using another algorithm, After that the image enhanced using optimized
median filter algorithm and remove Impurities that produced from first and second steps.
In this paper, we will design a Fuzzy Smith Predictor (FSP),
then we will model, simulate and analyze it using colored Fuzzy Petri
networks, then we will compare it with a conventional proportional
integral controller.
The main objective of this
research is to reduce the delay time
of the wind turbine system and to increase its reliability, in the other
side, to improve the response and stability of the operating point of
the mechanical energy and reduce vibration caused by the delay time
in the system.
In this article we propose a new graphical method for modeling
sequential controllers using high-level colored Petri nets. We will
present how to build a sequential controller using this method and
analyze its state space. The results in this stud
y showed an
advantage of the controller designed by the new method compared
to which designed algebraically by ordinary Petri net in complex
systems. The new method simplify the sequential controller network
and increase the performance speed and improve the reliability.
Stereoscopic broadcast Tv systems,That is,Those capable of reproducing a Three-dimensional picture,give a better idea about The televised scene,enhance artistic impression,and make The reproduction more realistic so That The observer has The sensatio
n of being actually present at The scene of action. For a compatible 2-d/3-d colour Tv system The channel bandwidth should be twice That of The standard broadcast Tv channel. The search for ways and means of reducing The required bandwidth without an impairment in The quality of The colour 3-d picture is a major direction in work or such systems.
This research aimed to recognition the effectiveness of program
proposed according to brainstorming method with using color print
images to acquiring the fourth grade students critical thinking
skills/classification, explanation, conclusion/ in social education .
