Computer
Haider Saeed Wdhayeh; Raghad Abdulaali Azeez; Athraa Jasim Mohammed
Abstract
In this paper, an algorithm to hide information in an image using QR code technology is presented. QR Code “QUICK RESPONSE CODE” is a two-dimensional array that can include different types of data and was first developed in 1993 for the Japanese Toyota Corporation for the purpose of tracking ...
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In this paper, an algorithm to hide information in an image using QR code technology is presented. QR Code “QUICK RESPONSE CODE” is a two-dimensional array that can include different types of data and was first developed in 1993 for the Japanese Toyota Corporation for the purpose of tracking products through production and marketing. The researchers paid great attention to QR code technology especially in the field of information security. The proposed algorithm in this paper hides the secret text in the image in a random way by generating random positions and using the LSB “Least Significant Bit” method. After that, the random positions are saved in the QR code file, and this is the hiding stage. In the extraction stage, the QR code file is read first to extract the positions where the secret text has been hidden. After that, the secret text is read according to the LSB method. The algorithm was implemented using the C-Sharp programming language and Microsoft Visual Studio 2019 development environment. After conducting experiments on a number of images and extracting results based on the PSNR “Peak signal-to-noise ratio “test method, the results were good and the algorithm is very strong against a brute force attack. This algorithm can be used in building authentication systems.
Computer
Maryam Raad Shihab; Rana Fareed Ghani; Athraa Jasim Mohammed
Abstract
The traffic surveillance system is a type of intelligent system of traffic control. Traffic control provides solutions to most problems faced by people. It helps to monitor, detect traffic congestion and traffic accidents. As science evolved, it became possible to control traffic using video surveillance. ...
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The traffic surveillance system is a type of intelligent system of traffic control. Traffic control provides solutions to most problems faced by people. It helps to monitor, detect traffic congestion and traffic accidents. As science evolved, it became possible to control traffic using video surveillance. Video surveillance is the most economical option that does not involve high costs or changes in infrastructure. Vehicle detection is one of the main parts of the traffic surveillance system. In this paper, vehicles will be detected using two different artificial intelligence methods (the YOLO method and the HAAR cascade classifier method). The first one is smarter than the second method, and both of them contain machine learning. The first processing step will read the video. Then vehicle detection algorithms are applied using two different ways. The comparison between them depends on the results to find the most effective and applicable vehicle detection method. After implementing the two methods, results were obtained using YOLO, that the accuracy is 91.31% and the error rate is 8.69%, in time 10 sec. As for using the XML (HAAR cascade classifier method) method, the accuracy is 86.9%, the quality is 86.9%, completeness is 90.9%, and the error rate is 13%, in time 17 sec. Thus, we conclude that the YOLO method has better results than the second method.