<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi

TThe property of 134−140Neodymium nuclei have been studied in framework Interacting Boson Model (IBM) and a new method called New Empirical Formula (NEF). The energy positive parity bands of 134−140Nd have been calculated using (IBM) and (NEF) while the negative parity bands of 134−140Nd have been calculated using (NEF) only. The E-GOS curve as a function of the spin (I) has been drawn to determine the property of the positive parity yrast band. The parameters of the best fit to the measured data are determined. The reduced transition probabilities of these nuclei was calculated. The critical point has been determined for 140Nd isotope. The potential energy surfaces (PESs) to the IBM Hamiltonian have been obtained using the intrin

Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com