Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

A new Schiff base ligand Bis-1,4-di[N-3-(2-hydroxy-1-amino)- acetophenonylidene] benzylidene [L] and its complexes with (Mn(II) ,Co(II) ,Ni(II and Cu(II)) were synthesized . The ligand was prepared in two steps. In the first step a solution of (terphthalaldehyde) in methanol reacts under reflux with (p-aminoacetophenone) to give an intermediate compound [1-[3-({4-[(3-Acetyl-phenylimino)-methyl]-benzylidene}-amino)-phenyl]- ethanone which reacts in the second step with (2-Amino-phenol) giving the mentioned ligand. The complexes were synthesized by addition the corresponding metal salt solution to the solution of the ligand in methanol under reflux in (1:1) metal to ligand ratio. On the basis of, molar conductance, I.R., UV-Vis, HPLC, chlorid