الفهرس 
Comparative Studies and Developments of Different Methods for Image Processing
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Abstract
Image processing [1, 2] is the technique of converting an image into its digital
format and performing manipulations on it to enhance its quality or to extract
some valuable information from it. Many different techniques were introduced
to perform different tasks on the image. Recently many new approaches are
introduced which are inspired from nature (Bio-inspired). They follow the
principle of charles Darwin of “Survival of Fittest”. The solutions which are
best among vast pool of solutions are only forwarded to next generation or next
iteration step and rest are discarded. Neural Network are shapes of Bio-inspired
techniques. [1, 3, 19]. Traditional methods and Bio-inspired techniques works
in the area of image processing, specially convolution neural network which
can be applied in the field of enhancement techniques of images for example:
image segmentation using edge detection [8, 9,21], content based image
retrieval [10] and image restoring [11, 12]. In some or the other aspect these
algorithms have enhanced the performance of each image processing
application, these techniques are gaining more interest day by day due to their
effective performance in every research domain [13]. In this thesis, we study
some methods for solving this ill-posed problem which is the segmentation of
images. In addition, introduce a new segmentation method for the breast and
evaluate the effectiveness by solving the problem of detecting breast cancer
from thermal images, comparative studies are presented. Parts of this thesis
were published and presented in 9th Cairo International Biomedical
Engineering Conference (CIBEC).