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RISS 인기검색어
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- 저자 : Ihab Zaqout (검색결과 3 건)
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Diagnosis of Skin Lesions Based on Dermoscopic Images Using Image Processing Techniques
Ihab S. Zaqout 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.9
Great effort has been put into the development of diagnosis methods for the most dangerous type of skin diseases - Melanoma. This paper aims to develop a prototype capable of segment and classify skin lesions in dermoscopy images based on ABCD rule. The proposed work is divided into four distinct stages: 1) Pre-processing, consists of filtering and contrast enhancing techniques. 2) Segmentation, thresholding and statistical properties are computed to localize the lesion. 3) Features extraction, Asymmetry is calculated by averaging the calculated results of the two methods: Entropy and Bi-fold. Border irregularity is calculated by accumulate the statistical scores of the eight segments of the segmented lesion. Color feature is calculated among the existence of six candidate colors: white, black, red, light-brown, dark-brown, and blue-gray. Diameter is measured by the conversion operation from the total number of pixels in the greatest diameter into millimeter (mm). 4) Classification, the summation of the four extracted feature scores multiplied by their weights to yield a total dermoscopy score (TDS); hence, the lesion is classified into benign, suspicious, or malignant. The prototype is implemented in MATLAB and the dataset used consists of 200 dermoscopic images from Hospital Pedro Hispano, Matosinhos. The achieved results shows an acceptable performance rates, an accuracy 90%, sensitivity 85%, and specificity 92.22%.
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Ihab Zaqout,Samar Elhissi,Aya Jarour,Heba Elowini 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.10
As mobiles become cheaper and gain popularity, mobile applications are developing quickly and trying to utilize more techniques to make these applications more efficient and usable. Augmented reality is a live direct or indirect view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. This research develops an android mobile application that utilizes real-time image processing techniques to provide simulated functionality to a hand drawing of piano keys. A piano keyboard with fourteen white keys and ten black keys is drawn used a black thick pen on paper, and the mobile is set in an angel that gives the optimum view of the piano keyboard when the camera is turned on. When the application is started, a camera shot of the piano, without the presence of hands or fingers in the view, is taken. The user can then start playing on his drawn piano. The application detects keystrokes and decides which key is pressed; and then plays the corresponding tone. The application is developed using OpenCV library which focuses on real-time image processing and computer vision, since the target devices with android platform, a Java program is used to port the C++ code to android. The application is tested on multiple android-based devices with different specifications under good lighting conditions. The empirical results are impressive and comparable across different devices, despite all changes in lighting and background; all devices exhibited the same level of accuracy in detecting fingers and drawn pianos.
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Samy Abu Naser,Ihab Zaqout,Mahmoud Abu Ghosh,Rasha Atallah,Eman Alajrami 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.2
In this paper an Artificial Neural Network (ANN) model, for predicting the performance of a sophomore student enrolled in engineering majors in the Faculty of Engineering and Information Technology in Al- Azhar University of Gaza was developed and tested. A number of factors that may possibly influence the performance of a student were outlined. Such factors as high school score, score of subject such as Math I, Math II, Electrical Circuit I, and Electronics I taken during the student freshman year, number of credits passed, student cumulative grade point average of freshman year, types of high school attended and gender, among others, were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was developed and trained using data spanning five generations of graduates from the Engineering Department of the Al- Azhar University, Gaza. Test data evaluation shows that the ANN model is able to correctly predict the performance of more than 80% of prospective students.
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