Today, there are large amounts of geospatial data available on the web such as Google Map (GM), OpenStreetMap (OSM), Flickr service, Wikimapia and others. All of these services called open source geospatial data. Geospatial data from different sources often has variable accuracy due to different data collection methods; therefore data accuracy may not meet the user requirement in varying organization. This paper aims to develop a tool to assess the quality of GM data by comparing it with formal data such as spatial data from Mayoralty of Baghdad (MB). This tool developed by Visual Basic language, and validated on two different study areas in Baghdad / Iraq (Al-Karada and Al- Kadhumiyah). The positional accuracy was asses

In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256)  in our research, compressed them by using MLP for each

Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

Image Fusion Using A Convolutional Neural Network