Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

WA Shukur, journal of the college of basic education, 2011 The aim of this research is designing and implementing proposed steganographic method. The proposed steganographic method don’t use a specific type of digital media as a cover but it can use all types of digital media such as audio, all types of images, video and all types of files as a cover with the same of security, accuracy and quality of original data, considering that the size of embedded data must be smaller than the size of a cover. The proposed steganographic method hides embedded data at digital media without any changing and affecting the quality of the cover data. This means, the difference rate between cover before hiding operation and stego is zero. The proposed steg

Modern digital technologies have affected the means of communication in terms of structure, function and methods of dealing with them, and the communication process has changed, becoming bilateral, reciprocal and interactive, after it was one-way and limited in circulation and the roles changed, so the receiver became the sender and reversed is correct, and the culture of the active user and the participant spread, and the communication process became continuous.
The international information network has provided new electronic channels in the media and communication that are not known and opened a new era for these means, which led to a trend towards digital media in an unprecedented way.
The new communication platforms are the re

Organic light emitting diodes (OLEDs) were fabricated containing host molecule of conjugated polymer MEH-PPV poly (2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenlenevinylene) which was dissolved in chloroform solvent and doped with guest molecules MWCNTs that were dissolved in DMF solvent with different volume ratios 0.05 and 0.15, nanocomposite system which acts as active layer in OLEDs device. The Poly(3,4-ethylenedioxythiophene):poly-(styrenesulfonate) "PEDOT:PSS" and Tris98-hydroxyquinoline) aluminum "Alq3" as hole transport layer HTL and electron transport layer ETL were used respectively, to enhanced the injection charge from the electrodes to the active layer. Spin coating method used for achieving facile and low cost OLED. The absorption s