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<\/p>\n","protected":false},"excerpt":{"rendered":"Discussion of a high diploma thesis in the College of Computer Science and Mathematics – Department of Software entitled:<\/p>\n
\u201cHiding information in an Adaptive Edge of image\u201d<\/p>\n
<\/p>\n
In continuation of the scientific research movement and with the follow-up and presence of the Dean of the College of Computer Science and Mathematics<\/p>\n
Respected Professor Dr. Duha Bashir Abdullah<\/p>\n
It was discussed in the discussion hall of the College of Computer \u00a0Science and Mathematics at the University of Mosul on Tuesday 20\/2\/2024<\/p>\n
Diploma\u2019s thesis by<\/p>\n
Noor Ghassan Abdullah Abdulrahman Al-Mady<\/p>\n
supervised by Assis. Prof.\u00a0 Shahd Abdulrahman Hasso<\/p>\n
The study dealt with an adaptive algorithm for hiding messages in colored images RGB. The proposed algorithm uses the regions of noise in the image to embed data, reducing tangible visual distortion. The Bit-Plane Complexity Segmentation (BPCS) algorithm is employed, where noise regions in the image are detected using the complexity measure \u03b1. Subsequently, the message embedded in the noise region in the bit levels for RGB channels. The proposed BPCS method used in this research modified. The search for the optimal threshold value conducted based on image data and message size. This determined threshold value adopted to distinguish between noisy and non-noisy regions in the most impactful bit planes: the fourth, fifth, sixth, seventh, and eighth. Another threshold value calculated from these for distinguishing noise from non-noise in the less impactful bit planes: the first, second, and third. Additionally, the first threshold value is encrypted using the RSA algorithm and hidden within the image along with the message. Upon retrieval and decryption, the second threshold value computed from it. The proposed algorithm implemented in Python and evaluated based on various factors: Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) using seven RGB images from the USC-SIPI image database, internet images, and real-world images. The results indicate that the algorithm provides high capability in hiding data in cover images without distorting the quality of the resulting image, achieving values of (PSNR\u226540), (MSE\u22645.34), and (SSIM\u22650.9781) for a message size of 14,368,512 bits in an image of size 1920*1080*3. The results also show that the proposed algorithm outperforms similar methods.<\/p>\n
The study aims to develop a technique for hiding information within RGB images in an adaptive manner that achieves an appropriate level of security and robustness while preserving the visual integrity of the image. Additionally, it aims to investigate the impact of various image characteristics such as color space and image size on the embedding, extraction, and hiding processes, while concealing a significant amount of data relatively without distorting the image.<\/p>\n
The discussion committee consists of<\/p>\n
Assis. Prof. Dr. Ahmed Sami Nourid\u2013 Chairman<\/p>\n
Assis. Prof. Hanan Hamed Ali \u2013 Member<\/p>\n
Assis. Prof.\u00a0 Shahd Abdulrahman Hasso\u2013 Member and supervisor<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
Discussion of a high diploma thesis in the College of Computer Science and Mathematics – Department of Software entitled: \u201cHiding information in an Adaptive Edge of image\u201d In continuation of the scientific research movement and with the follow-up and presence of the Dean of the College of Computer Science and Mathematics Respected Professor Dr. Duha Bashir Abdullah It was discussed in the discussion hall of the College of Computer \u00a0Science and Mathematics at the University of Mosul on Tuesday 20\/2\/2024 Diploma\u2019s thesis by Noor Ghassan Abdullah Abdulrahman Al-Mady supervised by Assis. Prof.\u00a0 Shahd Abdulrahman Hasso The study dealt with an [Read More]<\/a><\/p>\n","protected":false},"author":24,"featured_media":37952,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-37951","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-viva"],"_links":{"self":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts\/37951","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/users\/24"}],"replies":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/comments?post=37951"}],"version-history":[{"count":1,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts\/37951\/revisions"}],"predecessor-version":[{"id":37955,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts\/37951\/revisions\/37955"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/media\/37952"}],"wp:attachment":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/media?parent=37951"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/categories?post=37951"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/tags?post=37951"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}