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 cephalometric radiographs for adults with age range from 22-43 years old (51 males, 62 females), using certain linear and angular craniofacial measurements with the aid of computer program “AutoCAD 2007” Results: The eleven parameters measured for males and females when compared are statistically significantly different. All cranio-cephalometric measurements gave overall predictive accuracy of sex determination by discriminant analysis (86.7%). The stepwise selection method gave overall predictive accuracy of sex determination by discriminant analysis (85.8%). Age showed no statistical difference among the studied age range except for the distance from Mastoid to Frankfort plane. Conclusion: The lateral cephalometric measurements of craniofacial bones are useful to support sex determination of Iraqi population in forensic radiographic medicine.
The study was performed to isolate and identify the Myxococcus fulvus from the one hundred samples of soils of farms. Special growth conditions had been used to support the growth of M.fulvus local isolates and suppressed the growth of other microorganisms like (Drying , High Temperature , High concentration of antibiotics and specific growth media ) M.fulvus isolates had been subjected to the morphological, cultural , biochemical examination for identification , as well as , study the inhibitory activites of cells and filtrates of localized isolates against some pathogenic fungi include (Trichophyton mentagrophytes , Microsporum gypseum , Aspergillus niger and Fusarium oxyporum ) by using three methods :- Cup assay , well diffusio
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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
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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
... Show MoreImage Fusion Using A Convolutional Neural Network
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Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and
... Show MoreMany image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o
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