In this paper  new algorithm for  speeding up fractal image compression  is presented. A new adapted method based on computing the highest value of the pixel of the image to reduce the computational complexity in the encoder stage and which are led to decreasing the encoding time while the reconstructed image from the work as good as we want. For increasing the effectiveness of search stage we used another type of partitioning method that led to increase the flexibility of range partition, this method is HV-partition. We applied this method on images and also present a comparison of this method against other method which used to speed the fractal compression.

Gout skin detection and tracking has been the topics of an extensive research for the several past decades. Many heuristic and pattern recognition based strategies have been proposed for achieving robust and accurate solution.This paper demonstrates how a Gout skin detection recognition system can be designed with artificial neural network. Note that the training process did not consist of a single call to a training function. Instead, the network was trained several times on various input ideal and noisy images, the images which contents Gout skin . The objective of this study was to develop a back propagation artificial neural network (ANN) model that could distinguish gout image by several parameters for testing are Energy , Entropy , Average andVariance. Although only the color indices associated with image pixels were used as inputs, it was assumed that the ANN model could develop the ability to use other information, such as shapes, implicit in these data. The 756x504 pixel images were taken in the field and were then cropped to 100x100-pixel images in testing phase. A total of 80 images of gout image and other images were used for training purposes. For ANNs, the success rate for classifying gout image was as high as 100%.

In the present paper, a comparison  between classical masks and (odd and even) masks groups for Mycosis Fungoides disease Skin image edges detection is performed.The goal is to extract the information known in the image because it is vital to understand the image content as the proposed approach is the comparative edge by masks classical and a new set  of Groups  masks (odd and even ) which consist of 10 masks. The  database consists of 40 images reprints different  stage of the Mycosis Fungoides disease Skin images 10 images for each stage. The experimental results confirm the effectiveness of the proposed system. and confirm the effectiveness of the proposed(odd and even) Groups masks.

This work discusses the compression objects ratio for Macromedia Flash File (SWF) Image by Wavelet functions for compression and there effect for Macromedia Flash File (SWF) Images compression . We discusses classification objects in Macromedia Flash (SWF) image in to nine types objects Action, Font,Image, Sound, Text, Button, Frame, Shape and Sprite. The work is particularly targeted towards wavelet image compression best case by using Haar Wavelet Transformation with an idea to minimize the computational requirements by applying different compression thresholds for the waveletcoefficients and these results are obtained in fraction of seconds and thus to improve thequality of the reconstructed image. The promising results obtained concerning reconstructed images quality as well as preservation of significant image details, while, on the other hand achieving highcompression rates and better image quality while DB4 Wavelet Transformation higher compression rates ratio without kept for image quality .

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