Background: Determination of sex and estimation of stature from the skeleton is vital to medicolegal investigations. Skull is composed of hard tissue and is the best preserved part of skeleton after death, hence, in many cases it is the only available part for forensic examination. Lateral cephalogram is ideal for the skull examination as it gives details of various anatomical points in a single radiograph. This study was undertaken to evaluate the accuracy of digital cephalometric system as quick, easy and reproducible supplement tool in sex determination in Iraqi samples in different age range using certain linear and angular craniofacial measurements in predicting sex. Materials and Method The sample consisted of 113of true lateral cepha

In this research, an analysis for the standard Hueckel edge detection algorithm behaviour by using three dimensional representations for the edge goodness criterion is presents after applying it on a real high texture satellite image, where the edge goodness criterion is analysis statistically. The Hueckel edge detection algorithm showed a forward exponential relationship between the execution time with the used disk radius. Hueckel restrictions that mentioned in his papers are adopted in this research. A discussion for the resultant edge shape and malformation is presented, since this is the first practical study of applying Hueckel edge detection algorithm on a real high texture image containing ramp edges (satellite image).

In the recent years, remote sensing applications have a great interest because it's offers many advantages, benefits and possibilities for the applications that using this concept, satellite it's one must important applications for remote sensing, it's provide us with multispectral images allow as study many problems like changing in ecological cover or biodiversity for earth surfers, and illustrated biological diversity of the studied areas by the presentation of the different areas of the scene taken depending on the length of the characteristic wave, Thresholding it's a common used operation for image segmentation, it's seek to extract a monochrome image from gray image by segment this image to two region (for

In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.

In this paper the behavior of the quality of the gradient that implemented on an image as a function of noise error is presented. The cross correlation coefficient (ccc) between the derivative of the original image before and after introducing noise error shows dramatic decline compared with the corresponding images before taking derivatives. Mathematical equations have been constructed to control the relation between (ccc) and the noise parameter.

Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

The study aimed to identify the treatment of the press image of the Great Return Marches in the French international news agency AFP by knowing the most important issues, their direction and the degree of interest in them. The study belongs to the descriptive research, and used the survey method, within the context of the content analysis method, and the researcher relied on the content analysis form tool and the interview tool to collect data. The study population is represented in the photos published by the French News Agency about the Great Return Marches during the period (end of March / 2018 until the end of November / 2019. The researcher chose an intentional sample using the Complete Census method. The study material represented