حل المسالة العكسية للكسوريات من خلال الاساليب التطويرية المثلى وتطبيقاتها
Author name:
شيماء سلمان عبد
Supervisor name:
نادية محمد غانم | نصيف جاسم الجواري
General topic:
Mathematics
Specific topic:
Mathematics
Degree:
Doctorate
University:
Mustansiriyah University - College Of Science - Department Of Mathematics
Language:
English
University location:
Baghdad
First pages:
27T1156 - p.pdf
Abstract:
Fractal image coding based on the inverse problem of an iterated function system plays an essential role in several areas of computer graphics and in many other interesting applications. Despite this method have received much attention because of its high resolution and fast decoding and many other advantages, but it has not been used widely because, it required high computation time in the encoding process. Genetic algorithm as an efficient optimization approach is highly used to solve such problems. In this study, this technique is improved and implemented, and another improvement that helps to optimize the search space in the target image is proposed, this is through reaching of global optimum in a single run. It is known as crowding method. The first use of this method in solving of fractal inverse problem shows acceptable result, especially, in reducing of the encoding time and obtaining of good quality images. Although, crowding method provides a satisfactory results in comparing to the original Jacquin and genetic algorithm techniques, but it concentrates on the best elements in the population of the search space. To support global exploration and prevent trapping in local optima, a new probability is added, which helps to satisfy diversity in the population selection from both the best and worst individuals. This is satisfied through proposing of a new diversity method to reduce being trapped in local optima, and improve the time complexity of the algorithm. The relation between searching for an optimum solution and playing music is known as harmony search algorithm (HAS). This algorithm is used in this study for the first time to solve fractal inverse problem. It has been proved that access to find music harmony corresponds to solving of an optimization problem searching for an optimal solution. In comparing to the original technique, the experiments on the three proposed approaches show their efficiency and effectivity In this study, a new method that combines fractal dimension (FD) which is an indicator of image complexity with the FIC scheme is proposed. Classifying images in databases according to their texture by using FD helps reduce the retrieval time of query images. The validity of the proposed method is evaluated using geosciences images. Result shows that the method is computationally attractive.
